3613 results for "*geneti*"

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• CLL Genome

  The Chronic Lymphocytic Leukemia (CLL) Genome Project aims to identify genetic alterations involved in the development and progression of the CLL, which are still unknown, with the objective of generating a comprehensive catalogue of genetic alterations in 500 independent tumours. The CLL Genome Project, as a contributing member of the International Cancer Genome Consortium (ICGC), has the purposes of creating diagnostic tools, discovering therapeutic targets and developing new strategies that will allow a customized therapy for CLL in order to make it more precise and effective. This study consists of two datasets. EGAD00001000023 described in the Nature paper (2011), Whole-genome sequencing identifies recurrent mutations in chronic lymphocytic leukaemia, and the dataset EGA00001000044 & & EGAD00001000083 described in the Nature (2011) paper, Exome sequencing identifies recurrent mutations of the splicing factor SF3B1 gene in chronic lymphocytic leukemia.Additional data generated within the ICGC-CLL genome project can be found in studies EGAS00001000374 and EGAS00001001306

  Study EGAS00000000092

• Clonal fitness inferred from timeseries modeling of single cell cancer genomes

  Progress in defining genomic fitness landscapes in cancer by copy number alterations (CNA) has been impeded by lack of single cell and timeseries sampling. We generated 42,000 single cell whole genomes (scWGS) from breast epithelium and primary triple negative breast cancer (TNBC) patient-derived xenografts (PDX) collected during multi-year time series. Using a Wright-Fisher population genetics model, we inferred reproducible CNA-defined clonal fitness dynamics induced by TP53 mutation and cisplatin chemotherapy, with accurate forecasting of experimentally enforced clonal competition dynamics. Drug treatment in three long-term serially passaged TNBC PDX resulted in cisplatin resistant clones that had shown low fitness in the untreated setting. By contrast high fitness clones from treatment naive controls were eradicated reflecting an inversion of the fitness landscape. Upon drug release selective pressure dynamics were reversed indicating a fitness cost of treatment resistance. Taken together, our findings reveal clonal fitness dynamics linked to CNA and therapeutic resistance in polyclonal tumours.

  Study EGAS00001004448

• Genetic landscape of pediatric Infant Acute Lymphoblastic leukemia

  We performed whole genome sequencing of tumor and normal DNA samples obtained from 22 infant ALL cases with MLL rearrangements. In addition, we sequenced 2 paired diagnostic-relapse samples. Using complementary pipelines, somatically acquired genetic changes were analyzed, including single nucleotide variations (SNVs), insertion/deletions, structural variations and copy number variations in the cancer genomes. In addition, exome sequencing was performed on paired diagnostic and normal DNA samples obtained from 20 cases of non-infant MLL rearranged leukemias and somatic mutations in the coding regions were identified.

  Study EGAS00001000246

• Submission 208 - study_title 1

  Submission 208 - description 1

  Study EGAS50000000321

• Contribution of allelic imbalance to colorectal cancer

  Point mutations in cancer have been extensively studied but chromosomal gains and losses have been more challenging to interpret due to their unspecific nature. Here we examine high-resolution allelic imbalance (AI) landscape in 1699 colorectal cancers, 256 of which have been whole genome sequenced (WGSed). The imbalances pinpoint 38 genes as plausible AI targets based on previous knowledge, and unbiased CRISPR-Cas9 knockout and activation screens identified altogether 79 genes within AI peaks regulating cell growth. Genetic and functional data implicates loss of TP53 as a sufficient driver of AI. The WGS highlights an influence of copy number aberrations on the rate of detected somatic point mutations. Importantly, the data reveal several associations between AI target genes, suggesting a role for a network of lineage-determining transcription factors in colorectal tumorigenesis. Overall, the results unravel the contribution of AI in colorectal cancer and provide a plausible explanation why so few genes are commonly affected by point mutations in cancers.

  Study EGAS00001002966

• The genomic landscape of lung adenocarcinoma in East Asians

  We performed exome sequencing of 210 and transcriptome sequencing of 181 LUADs of Chinese patients. For more details, please see publication "Genomic landscape of lung adenocarcinoma in East Asians" by Chen J. et. al. in Nature Genetics 2020. https://www.nature.com/articles/s41588-019-0569-6.

  Study EGAS00001002941

• Leukemia stem cell containing fractions

  Study EGAS00001004893

• Acute Myeloid Leukemia peripheral blood samples

  Study EGAS00001004896

• Accessibility Over Transposable Elements Reveals Genetic Determinants of Stemness Properties in Normal and Leukemic Hematopoiesis

  Study EGAS00001007191

• Mapping_gene_environment_interactions_in_macrophages

  Immune cells sense and respond to external stimuli such as pathogens and initiate an inflammatory response. Genetic variants altering the behaviour and responses of immune cells may inform the results of disease association studies and provide an insight into the regulation of immune response. Studies mapping quantitative trait loci (QTL) are usually performed in quiescent or naïve cells and therefore any variants with a condition-specific manner (e.g. those with an effect only detectable in a specific time-point after cell stimulation) are likely to remain undiscovered. So far, only a handful of studies have attempted to study QTL in multiple states and even on those studies the number of states has remained relatively low (<5). Only very recently Horst and colleagues published the largest study to date investigating the effect of host variable (e.g. age, sex, contraceptive use etc.) on protein levels in macrophages stimulated with 19 different conditions (Horst et al, 2016). This project aims to develop a high-throughput experimental platform to detect QTL in a large number of states using iPSC derived macrophages. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001002268

• Rna-Seq Leiomyosarcoma subtypes

  Leiomyosarcomas (LMS) are genetically heterogeneous tumors differentiating along smooth muscle lines. Currently, LMS treatment is not informed by molecular subtyping and is associated with highly variable survival. While disease site continues to dictate clinical management, the contribution of genetic factors to LMS subtype, origins, and timing are unknown. Here we analyzed 70 genomes and 130 transcriptomes of LMS, including multiple tumor regions and paired metastases. Molecular profiling highlighted the extremely early origins of LMS. Three specific subtypes of LMS develop from distinct lineages of smooth muscle cells. Of these, dedifferentiated LMS with high immune infiltration and tumors primarily of gynaecological origin acquired the highest burden of genomic mutation and are associated with worse survival. Homologous recombination defects lead to genome-wide mutational signatures, and a corresponding sensitivity to PARP and other DNA damage response inhibitors, suggesting a novel therapeutic strategy for LMS. Finally, by phylogenetic reconstruction, we present evidence that clones seeding lethal metastases arise decades prior to LMS diagnosis.

  Study EGAS00001004783

• The Genetic History of Greenlandic-European contact

  The Inuit ancestors of the Greenlandic people arrived in Greenland close to 1000 years ago. Since then, Europeans from many different countries have been present in Greenland. Consequently, the present-day Greenlandic population has ~25% of its genetic ancestry from Europe. In this study, we investigated to what extent different European countries have contributed to this genetic ancestry.

  Study EGAS00001004933

• Genetic regulation of gene expression in human brain cell types

  We leveraged single nuclei RNA-seq from 192 human brain samples to map cis-eQTLs in 8 brain cell types. We found extensive cell-type specific genetic effect on gene expression and integrated our results with GWAS to identify putative novel risk genes for brain disorders and the cell types in which the disease mechanisms are likely active.

  Study EGAS00001006345

• Prostate cancer ancestral genomic disparity

  Prostate cancer is characterised by significant global disparity; mortality rates in SubSaharan Africa are double to quadruple those in Eurasia. Hypothesising unknown interplay between genetic and non-genetic factors, tumour genome profiling envisages contributing mutational processes. Through whole-genome sequencing of treatment-naïve prostate cancer from 183 ethnically/globally distinct patients (African versus European), we generate the largest cancer genomics resource for Sub-Saharan Africa. Identifying ~2 million somatic variants, Africans carried the greatest burden. We describe a new molecular taxonomy using all mutational types and ethno39 geographic identifiers, including Asian. Defined as Global Mutational Subtypes (GMS) A–D, although Africans presented within all subtypes, we found GMS-B to be ‘African-specific’ and GMS-D ‘African-predominant’, including Admixed and European Africans. Conversely, Europeans from Australia, Africa and Brazil predominated within ‘mutationally-quiet’ and ethnically/globally ‘universal’ GMS-A, while European Australians shared a higher mutational burden with Africans in GMS45 C. GMS predicts clinical outcomes; reconstructing cancer timelines suggests four evolutionary trajectories with different mutation rates (GMS-A, low 0.968/year versus D, highest 1.315/year). Our data suggest both common genetic factors across extant populations and regional environmental factors contributing to carcinogenesis, analogous to gene-environment interaction defined here as a different effect of an environmental surrounding in persons with different ancestries or vice versa. We anticipate GMS acting as a proxy to intrinsic and extrinsic mutational processes in cancers, promoting global inclusion in landmark studies.

  Study EGAS00001006425

• DNA methylation atlas of normal human cell types

  DNA methylation is a fundamental epigenetic mark that governs chromatin organization, cell identity, and gene expression. Here we describe a human methylome atlas, based on deep whole-genome bisulfite sequencing allowing fragment-level analysis across thousands of unique markers for 39 cell types sorted from 205 healthy tissue samples. Replicates of the same cell-type are >99.5% identical, demonstrating robustness of cell identity programs to genetic variation and environmental perturbation. Unsupervised clustering of the atlas recapitulates key elements of tissue ontogeny, and identifies methylation patterns retained since gastrulation. Loci uniquely unmethylated in an individual cell type often reside in transcriptional enhancers and contain DNA binding sites for tissue-specific transcriptional regulators. Uniquely hyper-methylated loci are rare and are enriched for CpG islands, polycomb targets, and CTCF binding sites, suggesting a novel role in shaping cell type-specific chromatin looping. The atlas provides an essential resource for interpretation of disease-associated genetic variants, and a wealth of potential tissue-specific biomarkers for use in liquid biopsies.

  Study EGAS00001006791

• Epigenetic reprogramming shapes monocytes and heterologous T cell derived cytokine responses in BCG vaccination

  Study EGAS00001007498

• UCSF Pediatric Bithalamic Glioma Genome Project

  Brain tumors are the most common solid tumors of childhood, and the genetic drivers and optimal therapeutic strategies for many of the different subtypes remain unknown. We performed targeted next-generation sequencing of approximately 500 cancer-associated genes on a cohort of 13 pediatric bithalamic diffuse gliomas, a lethal brain tumor of childhood for which the genetic basis is largely unknown. We identified that bithalamic diffuse gliomas harbor frequent mutations in the EGFR oncogene in the absence of accompanying gene amplification and only rare histone H3 mutation. These EGFR mutations were either small in-frame insertions within exon 20 (intracellular tyrosine kinase domain) or missense mutations within exon 7 (extracellular ligand-binding domain). Accompanying alterations included frequent TP53 mutation, CDK6 amplification or CDKN2C mutation, and BCOR and BCORL1 mutation or deletion.

  Study EGAS00001004033

• Whole exome and transcriptome sequencing of biliary tract cancer

  To uncover the full repertoire of genetic and transcriptomic landscape of biliary tract cancer (BTC), we molecularly characterized BTC based on genetic and transcriptomic alteration profiles.

  Study EGAS00001000950

• Genome-wide Ancestry and Demographic History of African-Descendant Maroon Communities from French Guiana and Surname.

  The transatlantic slave trade (TAST) was the largest forced migration in world history. However, the origins of the enslaved Africans and their admixture dynamics remain unclear. To investigate the demographic history of African-descendant Marron populations, we generated genome-wide SNP data (4.3 million markers) from 107 individuals from three African-descendant populations in South America, as well as 124 individuals from six west African populations to complement underrepresented African data sets. Our study sheds additional light on the demographic consequences of the TAST and illustrates how genetic data can complement historical sources.

  Study EGAS00001002535

• Genomic landscape of oral cancers (Illumina RNA-Seq)

  Human papillomavirus (HPV) is a necessary but insufficient cause of a subset of oral squamous cell carcinomas (OSCC) that is increasing markedly in frequency. To identify contributory, secondary genetic alterations in these cancers, we used comprehensive genomics methods to compare 149 HPV-positive and 335 HPV-negative OSCC tumor/normal pairs. Different behavioral risk factors underlying the two OSCC types were reflected in distinctive genomic mutational signatures. In HPV-positive OSCC, the signatures of APOBEC cytosine deaminase editing, associated with anti-viral immunity, were strongly linked to overall mutational burden. By contrast, in HPV-negative OSCC, T>C substitutions in the sequence context 5’-ATN-3’ correlated with tobacco exposure. Universal expression of HPV E6*1 and E7 oncogenes was a sine qua non of HPV-positive OSCC. Significant enrichment of somatic mutations was confirmed or newly identified in PIK3CA, KMT2D, FGFR3, FBXW7, DDX3X, PTEN, TRAF3, RB1, CYLD, RIPK4, ZNF750, EP300, CASZ1, TAF5, RBL1, IFNGR1 and NFKBIA. Of these, many affect host pathways already targeted by HPV oncoproteins, including the p53 and pRB pathways, or disrupt host defenses against viral infections, including interferon and nuclear factor-B signaling. Frequent copy number changes were associated with concordant changes in gene expression. Chr. 11q (including CCND1) and 14q (including DICER1 and AKT1) were recurrently lost in HPV-positive OSCC, in contrast to their gains in HPV-negative OSCC. High-ranking variant allele fractions implicated ZNF750, PIK3CA and EP300 mutations as candidate driver events in HPV-positive cancers. We conclude that virus-host interactions cooperatively shape the unique genetic features of these cancers, distinguishing them from their HPV-negative counterparts.

  Study EGAS00001003237

• Malignant mesothelioma EWAS on European prospective study

  Study EGAS00001006432

• After the completion of CINECA, EUCANCan, and euCanSHare. What's next?

  CINECA, EUCANCan, and euCanSHare were part of the EUCAN Cluster, made up of six projects that received funding under the same Horizon 2020 call. All EUCAN projects (CINECA, EUCANCan, EUCAN-Connect, euCanSHare, Receptor Plus, and ReCoDID) were aimed at facilitating data reuse and knowledge discovery by enhancing data exchange and long-term collaboration in the health field. Here are some highlights about EGA’s contribution to these projects. CINECA: advances in Federated discovery and infrastructure for cohorts CINECA (Common Infrastructure for National Cohorts in Europe, Canada, and Africa) developed a federated cloud-based infrastructure for making genomic and biomolecular data accessible. The project has assembled a virtual cohort of 1.4 million individuals from sources such as the EGA, CanDIG and H3Africa. The EGA–CRG co-leaded a work package Work Package 1 on Federated Data Discovery and Querying. Beacon v2, championed by Jordi Rambla and Lauren Fromont, has been one of the central elements for the discovery of human genetic and phenotypic data. The EGA-CRG contributed to the development of a model for cohort discovery inside the Beacon v2 model. The team also delivered a Discovery Portal was implemented to explore cohorts and individuals of synthetic data. It is a UI that gathers a network of Beacons, a service for query expansion, and a visualisation tool. Have a look at the Discovery Portal UI, gathering a network of Beacons. You will find entities such as the Barcelona Supercomputing Center (BSC), BioData.pt and the European Genomic Data Infrastructure (GDI), among others. euCanSHare: facilitation of data access management This joint EU-Canada project aimed to build a European and Canadian FAIR platform for cardiovascular data sharing and analysis. The EGA’s tasks contributed to the development of the data management plan and data flows, main web-portal and interoperability protocols. An important part of the EuCanShare platform is the data access manager, a tool for the data owners to control the access to their sensitive datasets. We built a user-friendly interface for data access committees (data owners) to easily manage their data requests and access credentials. The data access portal facilitates the creation and internal organization of the data access committees as well as the linkage of data usage conditions to specific datasets. The interface includes filters for browsing requests and page to visualize the request history helping with the handling of data access requests. EUCANCan: toward a federation of clinical institutions in oncology The EUropean-CAnadian CANcer Network worked towards building a federated network to advance personalized medicine in oncology, by promoting the standard analysis, management and sharing of harmonized genomic and phenotypic data. The EGA led tasks on defining data flows and preparing an adapted infrastructure for long-term data storage and sharing. One of the key contributions was the conception of the EGA communities, offering standard and interoperable solutions for data discovery, processing, and sharing to projects and institutions that would like to manage and share data in the context of the EGA ecosystem. What's Next? The participation in projects such as CINECA, EUCANCan, and euCanSHare provide us with experience for future projects. We are happy to enhance data sharing and reuse, vital for advancing clinical and genomic research. The Discovery Portal is a wonderful proof of concept for the Beacon network. Next, we will finalise both the network and the user interface, and make sure it can be applied to more clinically-centred settings like hospitals. Most data hosted at the EGA are about cancer research. Currently, we contribute to building tools and infrastructure to empower oncology research in several European projects such as EUCAIM, EUCANIMAGE and EOSC4Cancer. We also do not lose sight of initiatives in the field such as the International Cancer Genome Consortium (ICGC) with the project ARGO, whose data model was adopted in EUCanCan.

  Blog cineca-eucancan-and-eucanshare-were-concluded-in-june

• The EGA at the International Congress of Human Genetics

  Today is the start of the International Congress of Human Genetics (ICHG). This event, hosted by the African Society of Human Genetics (AfSHG) and the Southern African Society for Human Genetics (SASHG), will reunite international experts to highlight how genomic technologies are being managed to address challenges generated by the current status of Human Health and Genomics. The European Genome-phenome Archive (EGA) will be at the Congress participating in workshops, meetings and talks where topics such as data access and discovery as well as the Federated EGA will be present. Data access and discovery In the context of the “Federated data analysis workshop“ that will be held the 26ᵗʰ, managed in the context of the CINECA project, a hands-on-session on Beacon v2 Discovery will be led by Mauricio Moldes. Another session on authorisation and data access will be presented by Mallory Freeberg and Coline Thomas, with and introduction by Thomas Keane. During the workshop, an end-to-end federated data analysis use case will be presented. Data access and discovery In the context of the “ Federated data analysis workshop“ that will be held the 26ᵗʰ, managed in the context of the CINECA project, a hands-on-session on Beacon v2 Discovery will be led by Mauricio Moldes. Another session on authorisation and data access will be presented by Mallory Freeberg and Coline Thomas, with and introduction by Thomas Keane. During the workshop, an end-to-end federated data analysis use case will be presented. During the last four years, CINECA has been identifying gaps in data sharing between Africa, Canada and Europe in order to build a federated solution for data access. Thomas Keane will present the project within the sessions happening the 24ᵗʰ. The Federated EGA at the ICHG A Federated EGA poster will be shown during the Poster Session 1 that will take place the 23ʳᵈ. The objective is to bring awareness of the European Genome-phenome Archive as a resource for permanent archive and secure data sharing. In this context, the network generated by the Federated EGA is key for cases where research data cannot be shared outside local jurisdictions. The Federated EGA was officially launched on 2022 with research institutes from five countries becoming the first nodes of this network. Nowadays, with more than 20 nodes preparing to join, it aims to become the largest human omics data sharing initiative towards understanding human health and disease. The H3Africa Initiative and the African research represented in the EGA 1.1% of the EGA studies include samples from African populations. Countries such as South Africa, Kenya, Uganda or Egypt, among others, are present in the 72.577 samples from African individuals archived at the EGA. 23 EGA datasets are managed by the Human Heredity and Health in Africa Initiative (H3Africa). This Initiative will celebrate its Consortium Meeting the 27ᵗʰ and 28ᵗʰ, back-to-back with the ICHG. H3ABioNet, the Pan African Bioinformatics Network for the H3Africa consortium, will also take this context to celebrate its 10-Year Symposium during the Congress. Members of the EGA team will attend both of them, as the H3ABioNet works in conjunction with H3Africa projects, to submit data to the European Genome-Phenome Archive.

  Blog the-ega-at-the-international-congress-of-human-genetics

• Shedding light over COVID-19 susceptibility and severity

  “One of the most remarkable features of SARS-CoV-2 infection is the variation in consequence ranging from asymptomatic to life-threatening” state the authors of the majestic Nature paper released in accelerated pre-view on July 2021. This variation in consequences represent not only an issue of burning medical relevance, but also a scientific and intellectual challenge for scientists around the globe. Researchers are known to be easily triggered by a challenge, and they recently demonstrated to be even better at double their efforts to focus on an urgent societal need. In this work led and coordinated by the COVID-19 Host Genetics Initiative (COVID-19 HGI), researchers gathered data from 49,562 cases and two million controls from 46 studies performed worldwide. The majority of the data has been deposited at the EGA, where 29 datasets have been collected under the study number EGAS00001005304. Data gathered from diverse sources conferred a huge robustness to the results. Genetic data from different ancestry origin were included in the analyses, even though data from patients with European origin was highly predominant (approx. 75%). Separated analysis of the different ancestries gave rise to relevant differences in the results, highlighting how important it is to take this aspect in consideration for future studies. Data from the individual studies was compiled into three categories according to COVID-19 severity for a meta-analysis: (a) critically ill cases (b) moderate or severe cases (c) all cases. They were paired with non-COVID-19-reported controls. All three analysis resulted in a total of 13 genetic loci associated with COVID-19 severity. Out of those, 9 loci associated specifically with critical illness, while 6 (a few overlapped) associated with moderated illness. Some genomic position matched previous findings. Interestingly, working with such an enormous amount of data allowed the depth to discriminate association with disease susceptibility vs severity, an issue of large medical relevance. Several loci mapped into biological relevant genes, like TYK2, PPP1R15A and FOXP4, previously implicated in immune response and/or lung functions. Researchers participating in the COVID-19 Host Genetics Initiative have worked in an unprecedented time-tight collaboration, prioritizing data sharing and collective results to tackle the pandemic affecting the world. The scientific community won’t miss any of the lessons to learn from this, and the EGA is ready to keep working to enable safe data sharing and fruitful collaborations.

  Blog covid-19-susceptibility-and-severity

• GCAT | Genomes for life

  The GCAT project is a prospective cohort study that was designed to recruit the general population of Catalonia, the north-east region of Spain. This study is a long-term genomic, environmental and lifestyle cohort project that aims to evaluate and track multiple pathologies as well as biologically related traits. By the end of 2017, the GCAT Study had recruited a total of 20 000 participants aged 40–65 years. Participants who agreed to take part in the study completed a self-administered computer-driven questionnaire, and underwent blood pressure, cardiac frequency and anthropometry measurements. For each participant, blood plasma, blood serum and white blood cells are collected at baseline. The GCAT Study has access to the electronic health records of the Catalan Public Healthcare System. Participants are followed biannually for/during, at least, 20 years after recruitment. Therefore, the GCAT Study offers a unique opportunity to integrate diverse data to allow the identification of novel relations among different biomarkers and conditions. Results may lead to the development of new genetic, genomic, epigenomic and proteomic diagnoses and screening tests, as well as new public health recommendations. The only currently available population-based prospective cohort study in Spain to the date, including more than 4899 genotyped participants and 800 whole genome sequences is now stored in the EGA archive under accession id EGAS00001003018.

  Blog gcat-genomes-for-life

• Providing access to COVID-19 data: one year later

  response efforts On 11 March 2020 the World Health Organization declared the novel coronavirus outbreak a global pandemic. Four months later, the European Genome-phenome Archive (EGA) released its first COVID-19 dataset. This dataset – single cell RNA and VDJ sequencing of B cells from 60 COVID-19 patients – showed that neutralizing antibodies could be identified by high-throughput sequencing in response to SARS-CoV-2 infection. That was one year ago. Today, the EGA provides access to fifteen COVID-19 datasets from researchers across seven countries in Asia, Europe, and North America. These studies represent almost 17,000 individuals and have resulted in at least sixteen publications and preprints. Researchers deposit controlled access COVID-19 data at EGA The global research community has come together rapidly to investigate the SARS-CoV-2 coronavirus and better understand the related disease, COVID-19. These research efforts generate valuable genetic and phenotypic data from patients and research participants that can be shared with approved researchers. The EGA enables sharing of this research data by providing a service for archiving and controlled distribution of sensitive data. Over the past year, the EGA has worked with researchers to archive and distribute COVID-19 data from high-throughput sequencing experiments, genotyping studies, and phenotypic information. These datasets investigate the immune system, blood, and cells and tissues of the lung, which are relevant for studying a contagious respiratory illness caused by a viral infection. *Study Spotlight. In January 2021, Ancestry.com demonstrated the utility of deep phenotyping based on self-reported outcomes from a large population of mild and asymptomatic COVID-19 cases. They identified genetic associations with eight COVID-19 phenotypes and showed distinct patterns of association, most notably related to the chr3/SLC6A20/LZTFL1 and chr9/ABO regions. The supporting data is available at the EGA to approved researchers and includes both genotype and phenotype data for 15,000 individuals. EGA collaborates with global COVID-19 community Since the coronavirus outbreak, the EGA has collaborated with other life science resources to support discovery and access to COVID-19 datasets. COVID-19 Host Genetics Initiative. With the NHGRI’s Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL) platform, the EGA enables sharing of individual-level genetic and phenotypic data from the COVID-19 Host Genetics Initiative (HGI). This initiative aims to generate, share, and analyze data from COVID-19 host genetics research projects to better understand the genetic determinants of COVID-19 susceptibility, severity, and outcomes. In response to COVID-19, the EGA actively supports COVID-19 data submissions and integration of data access and flow into the COVID-19-HGI analysis platform. *Study Spotlight. The COVID-19 HGI has combined individual-level data for 13,868 COVID-19 positive patients (N=7,167 hospitalized) from 17 cohorts in nine countries. The data were used to assess the association of the major common COVID-19 genetic risk factor (chromosome 3 locus tagged by rs10490770) with mortality, COVID-19-related complications, and laboratory values. The genotype and phenotype data for 10 of these cohorts is available at the EGA to approved researchers under accession EGAS00001005304. Fig 1: EGA COVID-19 studies are searchable in the European COVID-19 Data Portal alongside other COVID-19 and SARS-CoV-2 public datasets. European COVID-19 Data Portal. EGA-archived COVID-19 data are discoverable via the European COVID-19 Data Portal (Fig. 1), which brings together public and controlled access data to accelerate coronavirus research for the international community. By indexing all COVID-19-related data in one place, researchers can more easily discover relevant datasets of interest, thus increasing the “FAIRness” (Findability, Accessibility, Interoperability, Reusability) of this valuable data. Fig 2: SARS-CoV-2 viral sequences are imported from ENA and analysed in Galaxy to detect variants. Results are accessible to researchers through the COVID-19 Viral Beacon. COVID-19 Viral Beacon. The COVID-19 Viral Beacon tool was developed in collaboration with the European Nucleotide Archive and Galaxy to enable near real-time browsing of SARS-CoV-2 variability at genomic, amino acid, and motif levels (Fig. 2). The COVID-19 Viral Beacon allows researchers to (i) perform detailed searches about genomic variants, (ii) filter queries and find unique cases, (iii) filter data based on strain-specific variants, and (iv) explore associated metadata. It uses the Global Alliance for Genomics and Health (GA4GH) Beacon standard including new Beacon v2 features. With this tool, researchers can study intra-host mutations on genomic regions of interest, or trace any variant frequency over time using raw read data. More than 200,000 SARS-CoV-2 analysed genomic data files are now available to researchers for further exploration. Ongoing COVID-19 efforts at EGA Addressing the COVID-19 pandemic is a global effort. Federated resources are necessary to support transnational deposition, access, and analysis of sensitive COVID-19 host genetics and other related data. At the same time, many countries now have emerging personalized medicine programmes which are generating data from national or regional healthcare initiatives. These data are subject to more stringent information governance than research data and often must comply with national data protection legislation. To address this need, the Federated EGA was established to serve as the primary global resource for discovery and access of sensitive human omics and associated data consented for secondary use. The Federated EGA will comprise a network of national human data repositories and will implement community standards and common interfaces. Launching Federated EGA promises to accelerate not only global research efforts to understand, diagnose, and treat COVID-19, but also to foster data reuse, enable reproducibility, and accelerate biomedical and disease research to ultimately improve human health.

  Blog providing-access-to-covid-19

• The last addition to the list of clonal evolution studies in the EGA

  Tumours of different types may arise from a single cell with at least one malignant mutation. Accumulation of subsequent hits generates lineages of cells with different cancer transformation power; thus, every clone follows an autonomous evolution, and several clones may co-exist into the same solid or liquid tumour. Clonal evolution studies are not new: the conceptual power of this approach has been recognized since the early ’80, especially in leukaemia patients. Nonetheless, these studies greatly benefit from recent technological improvements -machineries and protocols-, which enable ever-increasing sequencing depth, allowing the detection of low frequency variants and consequently more tumour clones. Note: the figure belongs to the original paper and is owned by the authors. Researchers at the University of Kyoto in Japan, have indeed used state of the art knowledge to investigate the clonal evolution of chronic myeloid leukemia (CML) in a large panel of patients. CML progresses from a majoritarian benign chronic phase into an often fatal blast crisis phase. It is nowadays known that blast crisis are triggered by genetic instability and disrupted DNA repair, which lead to accumulation of DNA mutations. The use of thyrosine kinase inhibitors targeting the Philadelphia chromosome have enormously improved the treatment of blast crisis, nonetheless resistant patients are still a medical challenge. Yotaro Ochi and collegues used Whole Exome Sequencing of paired chronic phase and blast crisis samples to depict the genetic landscape of progression from the first to the second stage of the disease (as illustrated in their figure). Their results were published in Nature Communication on this May 2021. They used a dataset previously deposited at the EGA (EGAS00001003071) and their new generated data have been made available under accession number EGAS00001005075. Their analysis of the occurring mutations contribute to understanding the mechanisms of CML evolution and therefore develop a protocol for early management of patients with a TKI resistance signature. Up to date, the EGA hosts 99 clonal evolution studies, developed in several cancer types, including myeloma, renal carcinomas and ovarian cancer, in addition to various leukaemia subtypes, where this approach has been more widely applied and produced important results and seminal papers. From a pan-cancer point of view, the definition of tumour architecture through clonal evolution studies is instrumental to unravel the mechanisms of disease progression and treatment-resistance insource. At the EGA, we are honoured to contribute to exciting and important science advances with our service!

  Blog the-last-addition-to-the-list-of-clonal-evolution-studies-in-the-ega

• The Federated EGA network

  In the last 10 years, most human omics data has been generated in the context of research consortia while recently there has been an emergence of large cohorts of human data generated by healthcare initiatives. Many countries in Europe now have nascent personalised medicine programmes. Thus, human genomics is shifting from being predominantly research-driven to being funded through healthcare systems. Genetic data generated in a healthcare context is subject to more stringent information governance than research data and nonetheless all data must adhere to national data protections laws. In this context, EGA identified the need for the development of a federated network to enable secure sharing of data whilst enabling genetic data to remain within the jurisdiction in which it was generated. The Federated EGA is designed to support national data management requirements for genomic and clinical data collected from citizens as part of healthcare or biomedical research projects. It includes a secure authorised access mechanism to support research use of these data across Europe and worldwide. We have engaged with over 14 ELIXIR countries to develop the federation model. The EGA federated configuration is composed of Central EGA, Federated EGA nodes and Community EGA nodes: Central EGA offers international submissions and helpdesk support, currently EGA co-managed by EMBL-EBI and CRG, Federated EGA nodes offer EGA services to researchers within their national jurisdiction, Community EGA nodes are individual institutions or initiatives with human genetic data intended to be shared with the research community. Key services available in the Federated EGA structure are: Central EGA Federated EGA node Community EGA nodes Data submission Offers international submissions service Offers submission service in a particular jurisdiction Does not offer an external submissions service Helpdesk support Provides external international helpdesk Provides helpdesk support for submitters in its jurisdiction and for approved users of data managed at its facilities Provides helpdesk support only for approved users of data managed at its facilities Data distribution Manages worldwide distribution for data hosted at Central EGA Manages worldwide distribution for data hosted at Federated EGA node Distribution for data hosted at Community EGA node EMBL-EBI and CRG have prepared a series of documents describing the overall governance and coordination framework. These describe the Federated EGA structure, the rights and responsibilities of the different parties and governing committees, and node operation guidelines. The federation governance proposal is under review by the first countries invited to join as Federated nodes, with further interested countries likely to join in the coming years. The Central EGA team has been working closely with many ELIXIR partners, including ELIXIR Finland, Luxembourg, Germany, Norway, Spain and Sweden.

  Blog the-federated-ega-network

• Data upcycling, powered by EGA

  In 2012 a collaborative effort headed by the teams of Carlos Caldas in Cambridge, UK and Samuel Aparicio, Canada, produced a pivotal study aimed at defining the mutational landscape of breast cancer. They gathered a collection of over 2000 breast cancer samples (METABRIC) associated with long-term clinical follow-up. They delineated an array of inherited and somatically acquired genetic variants and associated them to gene expression. This led to the identification of putative cancer-driving events and improved stratification of breast cancer patients. The study elicited huge attention and was tackled as herculean effort by fellow researchers. Cristina Curtis and her colleagues deposited the data in the EGA archive (EGAS00000000083). What they probably could not foresee is that their data would be reused more than 100 times, becoming one of the most downloaded datasets at EGA. In 2015, Frederik S. Varn and colleagues accessed the above-mentioned data from the New Hampshire, USA, to correlate it to transcriptional programs of hematopoietic cells infiltrated in breast tumours and found that those can influence patients' prognosis. Their findings, published in Nature Communications, improved the understanding of the interplay between immune system and cancer. Again, in 2017 the dataset was downloaded by an Italian/Polish collaboration and used to corroborate their mechanistic study that demonstrate how a long non-coding RNA (lncRNA) is aberrantly localized into the chromatin, where it modulates oncogenic isoforms expression, thus contributing to breast cancer. To date, the METABRIC dataset has been reused to contribute to 147 publications. Its impact on breast cancer research is incalculable, and it even spread beyond that, with recent contributions to the understanding of pan-cancer mechanisms and features. Some of the publications are translating into improvements in diagnosis and treatment of different types of breast cancer. This is just an example of how data upcycling can amplify the potential of any dataset, well past the scope of its creation, the imagination of its owners and any geographical border. At EGA, we are proud to empower such fruitful worldwide cycles of knowledge, providing a platform that enables safe sharing of sensitive genetic data.

  Blog data-upcycling-powered-by-ega

• Youth-GEMs, the project using data to define the mental health trajectories of young people

  Mental health trajectories are shaped by genetic, cognitive, social, and environmental factors that are particularly influential during human development. How exactly the interplay between these factors is impacting mental health, however, is yet unknown. The project “Gene Environment interactions in Mental health trajectories of Youth (Youth-GEMs)”, funded by the European Commission under the Horizon Europe programme, aims to help reducing mental suffering among European youth. How do Youth-GEMs contribute to bettering mental health in young people? Youth-GEMs aims to identify specific neurological, (epi)genetic and environmental drivers on mental health trajectories of young people. To do so, the project is working on a public knowledge base on functional genomics of the developing human brain, between birth and 24 years old. Reliable predictive models for trajectories of onset and course of mental illness in young people of the general population in Europe will be developed. Additionally, a secure and FAIR data infrastructure in mental health is being produced. Engaging and empowering young people Youth-GEMs is also working on the engagement of young people in the scientific field of Psychiatry. For that, the project is developing initiatives such as Science Café, intended to create a learning community where ideas and stories are shared. The 10th Science Café will take place today, with the participation of Lauren Fromont from the EGA. How do the EGA contribute to Youth-GEMs? The contributions require careful data management and harmonisation: we are dealing with an extraordinary amount of data types, sources, and time points (since the studies are longitudinal). To analyse them together and to determine which factors and interactions are truly key to account for mental health trajectories, the variables need to be transformed in a common “language”, i.e., harmonised under a common data model. Further, to guarantee FAIRness of data storage and sharing for future projects that will further advance our knowledge in the mental health field, we are ensuring that data are processed securely but can also be discovered easily. Find out more information about the project in the Youth-GEMs website.

  Blog youth-gems-mental-health

• From research to data sharing: exploring EGA user's experiences

  The Cell Plasticity and Regeneration Group at the Bellvitge Biomedical Research Institute-IDIBELL focuses on the process of recruitment of macrophages that takes place in the small intestine during injury and healing. They recently published a paper titled “Mucosal Macrophages Govern Intestinal Regeneration in Response to Injury" in Gastroenterology Journal. As part of the research, some experiments were conducted using human intestinal organoid lines. These cells were processed for RNA sequencing, and the sequencing data were deposited at the EGA to be made available to the scientific community. When dealing with human genomic information, repositories must ensure the availability of the datasets while ensuring data protection. In this context, the European Genome-phenome Archive stands as a service for secure archiving and sharing of genetic, phenotypic and clinical data resulting from biomedical research. Following the recent publication of their paper, we took the opportunity to talk to Ilias Moraitis, first author, and Jordi Guiu, group leader, to find out about their experience with data sharing. Could you explain the focus of your research? In the lab, we study intestinal regeneration and how immune cells participate in this process. We use several techniques: engineered mouse models, image tracing, as well as mouse and human cells intestinal organoids. What challenges do you face regarding data management? We didn’t have a lot of problems. Always the informatic part, the data analysis, can give problems. But everything was smooth and working. We think it’s very important to deposit the data in repositories. For the mouse data it is very straightforward, but for us it was the first time depositing human data, which is sensitive because it comes from patients, and this is legally regulated. That’s why we thought about the EGA, and it was our first time. Why do you think it is important to submit data to repositories such as EGA? Because we think data is important for the science. Nowadays, we are sequencing a lot everywhere worldwide and having these resources shared with the scientific community it’s not only good for science, but it is also saving money and reducing costs. And there is so much data in there that can be used for other projects and for other questions. And it saves time! How was the process of submitting the data to the EGA? The communication worked very well but it was slower than we would like. But I think this is something we learn on the way. People usually wait until the last minute to do this before publication but if you know it in advance, you can start the process earlier. If you had to repeat the process, would you do anything differently? It’s like everything, isn’t it? For the first time you don’t know, you aren’t sure, but for the second time you know the steps, you know what to do and it’s faster. Of course, we would to do it earlier. Also, there were some things related to the control access that we didn’t know how to manage, but it was something more internal to us. Who is going to receive the communications and when, is our ethical committee going to evaluate this? All these technicalities that we didn’t know before starting this process, so we had to think about all these things. Next time it will be faster on our side. Do you have any suggestions for us to improve the submission process? Maybe we’ll need to ask our bioinformatician who did it! He was in charge of this part. Besides that, we think if the process were faster, it would be better for everyone. Also, in science a lot of times you have to do a lot of things at the very last minute, because of the nature of the experiments, or the need to accomplish for submitting a paper. Being faster in the process would be a plus. On your side, we went through the process and were able to find some information, but there were aspects we weren't aware of and weren't sure how to handle. I'm not sure if other institutes have different protocols for managing data requests or how they handle these internally. We believe the main issue lies in how the forms are filled out. Do you have any recommendations for other submitters? The main advice is to do this with enough time. Submit the data when you have the sequences, and don’t wait until the last minute. And then it can be under embargo, so you don’t need to make it public at that moment. As soon as you sequence, upload it and then it will be there for whenever you need to publish. How do you think we could encourage other researchers to submit their data? There are different layers here. One is that it is mandatory. You have to do this. The other is that we belong to a research community, to the same community and sharing this is making our research community stronger and more efficient. And then, also because this gives you visibility. The data is there, other people can analyse your data, and this also will bring citations to your papers. It has many advantages.

  Blog from-research-to-data-sharing

• Understanding_the_multicellular_dynamics_of_clear_cell_renal_cell_carcinoma___single_cell_RNA_sequencing

  This study will reconstruct the single cellular phylogeny of tumour and immune cells in relation to both genomic, functional, and spatial location. 20 tumours in total will be studied, including non-progressing small renal masses, progressing small renal masses, relatively indolent larger tumours, and high risk tumour with metastatic sampling. We aim to: Generate a focused, comprehensive phylogenetic characterisation of tumour cells Understand the dependencies of the cancer genome, transcriptome, tissue architecture and the single cellular micro-environment Quantify the single cellular composition and functional intra- and inter- tumoural heterogeneity Determine the phylogeny of tumour associated lymphocytes and their relationship to neo-epitopes and the immune microenvironment Investigate the mechanisms by which the tumour-normal interface constrains tumoural growth

  Study EGAS00001003519

• ATAC-seq/ChIP part

  Epigenetics: ATAC-seq and ChIP-seq data

  Study EGAS00001006520

• Molecular heterogeneity and commonalities in pancreatic cancer precursors with gastric and intestinal phenotype

  Due to the limited number of modifiable risk factors, secondary prevention strategies based on early diagnosis represent the preferred route to improve the prognosis of pancreatic ductal adenocarcinoma (PDAC). Here, we provide a comparative morphogenetic analysis of PDAC precursors aiming at dissecting the process of carcinogenesis and tackling the heterogeneity of preinvasive lesions.

  Study EGAS00001006793

• Transcriptomic and epigentic analysis of human peripheral blood NK cell subsets revealing role of Bcl11b in differentiation

  Transcriptomic analysis of seven human peripheral blood NK cell subsets and three T cell subsets purified from healthy cytomeglovirus seropositive donors. Epigenetic analysis including identification of open chromatin and active enhancer elements confirms key regulatory factors defining an NK cell differentiation axis. Chromatin-immunoprecipitation sequencing reveals contribution of key transcription factors associated with NK cell differentiation including Bcl11b.

  Study EGAS00001005025

• BLUEPRINT Hematopoietic Stem/Progenitor Cell Methylomes

  Study EGAS00001002070

• RNA-seq of Liver Cancer

  The French ICGC project on liver tumors is coordinated by Pr Jessica Zucman-Rossi and funded by Inca (French Institute for Cancer). The aim of the present project is to identify the catalog of somatic and germline mutations in liver tumors using whole genome (WGS) and whole exome sequencing (WGS), integrated with DNA methylation and RNA sequencing (RNA-seq) data. The present series corresponds to 161 RNA-seq samples from tumors with matched WES or WGS. Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

  Study EGAS00001002879

• Whole Exome Sequencing of 60 tumor/normal matched liver Cancers (HCC)

  The French ICGC project on liver tumors is coordinated by Pr Jessica Zucman-Rossi and funded by Inca (French Institute for Cancer). The aim of the present project is to identify the catalog of somatic and germline mutations in liver tumors using whole genome (WGS) and whole exome sequencing (WGS), integrated with DNA methylation and RNA sequencing (RNA-seq) data. The present series corresponds to 60 whole exome tumor/normal pairs with matched RNA-seq. Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

  Study EGAS00001003063

• Exome sequencing of advanced hepatocellular carcinoma

  The aim of our project is to decipher the genomic of advanced hepatocellular carcinoma using whole exome sequencing. To this purpose, we aim to compare genetic landscape of advanced hepatocellular carcinoma with early tumor in order to understand the mechanisms of tumor progression. This work will also help to identify new therapeutic targets potentially useful to treat patients at advanced stage. This study contain whole exome sequencing aligned reads for 41 tumor with matched normal samples

  Study EGAS00001003130

• Coding and non-coding drivers of mantle cell lymphoma identified through exome and genome sequencing

  Mantle cell lymphoma (MCL) is an uncommon B-cell non-Hodgkin lymphoma (NHL) that is incurable with standard therapies. The genetic drivers of this cancer have not been firmly established and the features that contribute to differences in clinical course remain limited. To extend our understanding of the biological pathways involved in this malignancy, we performed a large-scale genomic analysis of MCL using data from 51 exomes and 34 genomes alongside previously published exome cohorts. To confirm our findings, we re-sequenced the genes identified in the exome cohort in 191 MCL tumors, each having clinical follow-up data. We confirmed the prognostic association of TP53 and NOTCH1 mutations. Our sequencing revealed novel recurrent non-coding mutations surrounding a single exon of the HNRNPH1 gene. In RNA-seq data from 103 of these cases, MCL tumors with these mutations had a distinct imbalance of HNRNPH1 isoforms. This altered splicing of HNRNPH1 was associated with inferior outcomes in MCL and showed a significant increase in protein expression by immunohistochemistry. We describe a functional role for these recurrent non-coding mutations in disrupting an auto-regulatory feedback mechanism, thereby deregulating HNRNPH1 protein expression. Taken together, these data strongly implicate a role for aberrant regulation of mRNA processing in MCL pathobiology.

  Study EGAS00001004289

• Genetic and evolutionary patterns of treatment resistance in relapsed B-cell lymphoma

  Study EGAS00001004469

• Targeting AXL Kinase Uniquely Sensitizes Therapy-Insensitive Leukemic Stem and Progenitor Cells to Venetoclax Treatment in Acute Myeloid Leukemia

  The abundance of genetic abnormalities and phenotypic heterogeneities in AML pose significant challenges to developing improved treatments. Here we demonstrated that a key GAS6/AXL axis is highly activated in AML patient cells, particularly in leukemic stem cells. We developed a potent, selective AXL inhibitor that has excellent pharmaceutical properties and efficacy against preclinical patient-derived xenotransplantation models of AML. Importantly, inhibition of AXL sensitized AML stem/progenitor cells to venetoclax treatment, with strong synergistic effects in vitro and in vivo. Mechanistically, single-cell RNA-sequencing and functional validation studies uncovered that AXL inhibition or in combination with venetoclax potentially targets intrinsic metabolic vulnerabilities of AML stem/progenitor cells, which shows a distinct transcriptomic profile and inhibits mitochondrial oxidative phosphorylation. These findings have direct translational impact on the treatment of AML and other cancers with high AXL activity.

  Study EGAS00001004663

• BLUEPRINT ChIP-seq data for cells in the haematopoietic lineages, from adult and cord blood samples.

  ChIP-seq data for cells in the haematopoietic lineages, from adult and cord blood samples.

  Study EGAS00001000326

• Whole Genome Sequencing of HCC

  The French ICGC project on liver tumors is coordinated by Pr Jessica Zucman-Rossi and funded by Inca (French Institute for Cancer). The aim of the present project is to identify the catalog of somatic and germline mutations in liver tumors using whole genome (WGS) and whole exome sequencing (WGS), integrated with DNA methylation and RNA sequencing (RNA-seq) data. The present series corresponds to 24 whole genome sequencing (12 Tumoral/Non-tumoral pairs). Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

  Study EGAS00001002888

• Exome sequencing of hepatocellular carcinomas identifies new mutational signatures and potential therapeutic targets

  Genomic analyses promise to improve tumor characterization in order to optimize personalized treatment for patients with hepatocellular carcinoma (HCC). Exome sequencing analysis of 243 liver tumors revealed mutational signatures associated with specific risk factors, mainly combined alcohol/tobacco consumption, aflatoxin B1 and HBV infection. We identified 161 putative driver genes associated with 11 recurrent pathways. Associations of mutations defined 3 groups of genes related to risk factors and centered on CTNNB1 (alcohol), TP53 (HBV) and AXIN1. Analyses according to tumor stage progression revealed TERT promoter mutation as an early event whereas FGF/CCND1 amplification, TP53 and CDKN2A alterations appeared at more advanced stages in aggressive tumors. In 24% of the tumors, we identified genetic alterations potentially targetable by FDA-approved drugs. In conclusion, we identified risk factor–specific mutational signatures and defined the extensive landscape of altered genes and pathways in HCC, which will be useful to design clinical trials for targeted therapy.

  Study EGAS00001001002

• De novo assembly of 150 Danish genomes reveals rich structural complexity

  Most known genetic variation in human genomes has been called from comparison of short reads to the reference genome, an approach biased against finding complex variation. We sequenced 150 individuals from 50 parent-offspring trios with multiple insert-size libraries to very high coverage. We show that each genome could be independently de novo assembled into a small number of high-quality scaffolds (median N50 > 21 Mb), each of quality comparable to long read assemblies while being very cost-effective. We show that our variant call set from comparing de novo assemblies is far more complete in terms of complex variation than previous studies. Importantly, even the complex 4-5 Mb extended MHC region was assembled and resolved into haplotypes, revealing >700kb novel sequence in this important region of the genome, and major parts of the Y chromosome including some palindromes were assembled with high accuracy. Finally, we show that our variant call-set allows for the genotyping of many more complex variants when used as a reference-panel for imputation into SNP-chip data or into previously resequenced genomes.

  Study EGAS00001002108

• Genetic and Functional Drivers of Diffuse Large B Cell Lymphoma

  Diffuse large B cell lymphoma (DLBCL) is the most common hematologic malignancy and is characterized by a striking degree of heterogeneity. We enrolled a total of 1001 DLBCL patients and comprehensively defined the landscape of genetic mutations, copy number alterations and expression through whole-exome and transcriptome sequencing. We identified 150 genetic drivers of DLBCL including many novel, clinically relevant genes (e.g. SPEN, SETD1B and KLHL14). Genetic drivers were highly enriched among essential genes identified by CRISPR screening in DLBCL cell lines including those of immediate potential therapeutic relevance such as MTOR, SYK, SF3B1 and XPO1. RHOA emerged as a critical driver gene from our genetic analysis and CRISPR screen; we further delineated its functional role in vitro and in vivo models to define its role as an essential oncogene in DLBCL. Our work thus identifies the functional landscape of genetic drivers and their clinical and therapeutic relevance in DLBCL patients.

  Study EGAS00001002606

• Summary statistics from genome-wide association study in glioma of 12,488 cases and 18,169 controls.

  Genome-wide association studies (GWAS) have transformed our understanding of glioma susceptibility, but individual studies have had limited power to identify risk loci. We performed a meta-analysis of existing GWAS and two new GWAS, which totaled 12,488 cases and 18,169 controls. We identified five new loci for glioblastoma (GBM) at 1p31.3 (rs12752552; P = 2.04 × 10-9, odds ratio (OR) = 1.22), 11q14.1 (rs11233250; P = 9.95 × 10-10, OR = 1.24), 16p13.3 (rs2562152; P = 1.93 × 10-8, OR = 1.21), 16q12.1 (rs10852606; P = 1.29 × 10-11, OR = 1.18) and 22q13.1 (rs2235573; P = 1.76 × 10-10, OR = 1.15), as well as eight loci for non-GBM tumors at 1q32.1 (rs4252707; P = 3.34 × 10-9, OR = 1.19), 1q44 (rs12076373; P = 2.63 × 10-10, OR = 1.23), 2q33.3 (rs7572263; P = 2.18 × 10-10, OR = 1.20), 3p14.1 (rs11706832; P = 7.66 × 10-9, OR = 1.15), 10q24.33 (rs11598018; P = 3.39 × 10-8, OR = 1.14), 11q21 (rs7107785; P = 3.87 × 10-10, OR = 1.16), 14q12 (rs10131032; P = 5.07 × 10-11, OR = 1.33) and 16p13.3 (rs3751667; P = 2.61 × 10-9, OR = 1.18). These data substantiate that genetic susceptibility to GBM and non-GBM tumors are highly distinct, which likely reflects different etiology.

  Study EGAS00001003372

• Targeted sequencing of follicular lymphoma tumour samples from the UK's Haematological Malignancy Research Network

  Follicular lymphoma displays morphological and clinical heterogeneity, underpinned by shared molecular pathogenesis. Mutations in epigenetic regulators alongside t(14;18) have been identified as disease initiating events. Additional mutational diversity suggests disease heterogeneity. Whether this resolves into mechanistically distinct subsets remains an open question. Targeted sequencing was applied to an unselected population-based FL cohort (n=548) diagnosed in a catchment population of ~4 million (14 centers), with full clinical follow-up (n=538) that included 96 DLBCL transformations. We investigated whether molecular subclusters of FL can be identified, and whether mutational data provide predictive information relating to transformation.

  Study EGAS00001005238

• Multimodal single-cell and bulk glioma analyses

  Glioma intratumoral heterogeneity enables adaptation to challenging microenvironments and contributes to therapeutic resistance. We integrated 914 single-cell DNA methylomes, 55,284 single-cell transcriptomes, and bulk multi-omic profiles across 11 adult IDH-mutant or IDH-wild-type gliomas to delineate sources of intratumoral heterogeneity. We show that local DNA methylation disorder associates with cell-to-cell DNA methylation differences, is elevated in more aggressive tumors, links with transcriptional disruption, and is altered in environmental stress response. Glioma cells under in vitro hypoxic and irradiation stress increased local DNA methylation disorder and shifted cell states. We identified a positive association between genetic and epigenetic instability that was supported in bulk longitudinally collected DNA methylation data. Increased DNA methylation disorder associated with accelerated disease progression, and recurrently selected DNA methylation changes were enriched for environmental stress response pathways. Our work identifies an epigenetically facilitated adaptive stress response process and highlights the importance of epigenetic heterogeneity in shaping therapeutic outcomes.

  Study EGAS00001005300

• UK10K COHORT ALSPAC

  The UK10K project proposes a series of complementary genetic approaches to find new low-frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome-wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein-coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will directly analyse quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. The Avon Longitudinal Study of Parents and Children (ALSPAC) is a two-generation prospective study. Pregnant women living in one of three health districts in the former county of Avon with an expected delivery date between April 1991 and December 1992 were eligible to be enrolled in the study, and this formed the initial point of contact for the development of a large, family based resource. Information has been collected on the children and the mothers through retrieval of biological materials (e.g. antenatal blood samples, placentas), biological sampling (e.g. collection of cord blood, umbilical cord, milk teeth, hair, toenails, blood and urine), self-administered questionnaires, data extraction from medical notes, linkage to routine information systems and at repeat research clinics.

  Study EGAS00001000090

• UK10K COHORT TWINSUK

  The UK10K project proposes a series of complementary genetic approaches to find new low-frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome-wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein-coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will directly analyse quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. The TwinsUK samples will be part of the cohort study and will undergo whole genome sequencing. For further information with regard to this cohort please contact Brent Richards (brent.richards@kcl.ac.uk) or Nicole Soranzo (ns6@sanger.ac.uk).

  Study EGAS00001000108

• Breast_Cancer_Somatic_Genetics_Study_

  We propose to definitively characterise the somatic genetics of ER+ve, HER2-ve breast cancer through generation of comprehensive catalogues of somatic mutations in 500 cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Study EGAS00001000195

• Transcriptome Analysis Offers a Comprehensive Illustration of the Genetic Background of Pediatric Acute Myeloid Leukemia

  Study EGAS00001003701

• SG10K_Pilot - Large-scale whole-genome sequencing of three diverse Asian populations in Singapore

  Underrepresentation of Asian genomes has hindered population and medical genetics research on Asians, leading to population disparities in precision medicine. By whole-genome sequencing of 4,810 Singapore Chinese, Malays, and Indians, we found 98.3 million SNPs and small insertions/deletions, over half of which are novel. Population structure analysis demonstrated great representation of Asian genetic diversity by three ethnicities in Singapore, and revealed a Malay-related novel ancestry component. Furthermore, demographic inference suggested that Malays split from Chinese ~24,800 years ago, and experienced significant admixture with East Asians ~1,700 years ago, coinciding with the Austronesian expansion. Additionally, we identified 20 candidate loci for natural selection, among which 14 harbored robust associations with complex traits and diseases. Finally, we showed that our data can substantially improve genotype imputation in diverse Asian and Oceanian populations. These results highlight the value of our data as a resource to empower human genetics discovery across broad geographic regions.

  Study EGAS00001003875

• Genomic_characterisation_of_MGUS__

  he hematological malignancy multiple myeloma (MM), also called Kahler’s disease or plasma cell (PC) myeloma, is characterized by a clonal expansion of PCs originating in the bone marrow (BM). The expansion of these cells leads to an overproduction of antibodies and results in typical symptoms such as anemia, renal failure and bone lesions. All cases of MM are preceded by the asymptomatic, non-malignant pre-stage monoclonal gammopathy of undetermined significance (MGUS). Of all MGUS patients, only 1% per year will progress to MM. Despite efforts to elucidate the molecular mechanisms underlying the MGUS-to-MM progression, its pathogenesis still remains largely unknown. Additionally, the genetic profiles of MGUS patients have only been limitedly investigated due to the only incidental finding of MGUS, the difficulties in BM sampling and isolating a sufficient number of aberrant PCs from the BM aspirates of MGUS patients. Consequently, reliable biomarkers to individually predict which MGUS patients will progress to MM and which will not, are lacking. Therefore, it is highly required to study the molecular pathogenesis of MGUS and the role of genetic events in relation to the malignant transformation to MM.

  Study EGAS00001004124

• Whole Genome Sequencing of 317 individuals from the Pacific region

  Although genetic studies of modern Oceanians have revealed varying levels of admixture with populations of East Asian ancestry, attributed to the Austronesian expansion, the early peopling history of Oceania remains poorly characterized. Additionally, it is currently unknown whether and how the settlement of the Pacific was accompanied by genetic adaptation to island environments, and if archaic introgression facilitated this process in Oceanians, who present the highest worldwide levels of combined Neanderthal and Denisovan ancestry. This study reports the first whole genome-based survey that addresses a wide range of questions related to the demographic and adaptive history of Pacific populations.

  Study EGAS00001004540

• Reconstruction of human phylogenetic trees using single-cell genome sequencing

  The trillions of cells that constitute the human body are developed from a fertilized egg through embryogenesis. However, cellular dynamics and developmental outcomes of embryonic cells remain to be largely unknown due to the technical and ethical challenges. Here we sequenced whole-genomes single-cell-derived clones and various bulk tissues dissected from entire human bodies. Using the discovered somatic mutations as an intrinsic barcode, we reconstructed cellular phylogenetic trees that provide novel insights into early human embryogenesis.

  Study EGAS00001004824

• Accurate detection and classification of pediatric sarcomas based on cell-free DNA fragmentation patterns

  Sequencing of cell-free DNA in the blood of cancer patients (“liquid biopsy”) provides attractive opportunities not only for early diagnosis, but also for minimally invasive monitoring of treatment response and disease courses. To unlock liquid biopsy analysis for pediatric tumors with few genetic aberrations, we developed an integrated genetic/epigenetic analysis method and applied it to 241 deep whole-genome sequencing profiles of 95 patients with Ewing sarcoma and 31 patients with other pediatric sarcomas. We achieved sensitive detection and classification of circulating tumor DNA in peripheral blood independent of any genetic alterations. We evaluated different metrics for cell-free DNA fragmentation analysis and developed LIQUORICE, a bioinformatic tool for detecting circulating tumor DNA based on tumor-specific chromatin structure. Using machine learning methods, we combined several fragmentation-based metrics into an integrated approach for liquid biopsy analysis tailored to cancers with low mutation rates but widespread epigenetic deregulation. Clinical associations highlighted the potential value of cfDNA fragmentation patterns as prognostic biomarkers in Ewing sarcoma. Additionally, we performed low coverage whole-genome-sequencing on 43 tumor biopsy samples from patients with Ewing sarcoma, in order to compare copy number aberrations detected in cell-free DNA and biopsy samples of the same patients. For validation of the epigenetic signatures inferred from cell-free DNA, we further performed reduced representation bisulfite sequencing (RRBS) on 38 matched biopsy samples from patients with Ewing sarcoma. In summary, our study provides a comprehensive analysis of circulating tumor DNA beyond recurrent somatic mutations, and it renders the benefits of liquid biopsy more readily accessible for childhood cancers.

  Study EGAS00001005127

• Reference epigenomes generated as part of the International Human Epigenomics Consortium (IHEC)

  The Centre for Epigenome Mapping Technologies (CEMT) is an epigenome sequencing platform funded by the Canadian Institutes of Health Research (CIHR) and Genome BC as part of the Canadian Epigenetics, Environment and Health Research Consortium (CEEHRC). CEMT aims to produce 100 human reference epigenomes, each comprising the following datasets: whole genome; whole genome bisulfite and oxidative bisulfite; transcriptome; microRNA; and chromatin immunoprecipitation (ChIP)-seq for the core chromatin marks (H3K4me1, H3K4me3, H3K9me3, H3K27me3, H3K36me3, and H3K27ac).CEEHRC is a full member of the International Human Epigenomics Consortium (IHEC), which aims to coordinate the production of 1,000 reference maps of human epigenomes for key cellular states relevant to health and diseases. As such, all datasets submitted by the CEMT platform conform to IHEC assay standards and metadata guidelines.

  Study EGAS00001000552

• The double-hit signature identifies double-hit diffuse large B-cell lymphoma with genetic events cryptic to FISH​

  High-grade B-cell lymphomas with MYC and BCL2 and/or BCL6 rearrangements (HGBL-DH/THs) include a group of diffuse large B-cell lymphomas (DLBCLs) with inferior outcomes after standard chemoimmunotherapy. We recently described a gene expression signature that identifies 27% of germinal center B-cell DLBCLs (GCB-DLBCLs) as having a double-hit-like expression pattern (DHITsig) and inferior outcomes; however, only half of these cases have both MYC and BCL2 translocations identifiable using standard breakapart fluorescence in situ hybridization (FISH). Here, 20 DHITsig+ GCB-DLBCLs apparently lacking MYC and/or BCL2 rearrangements underwent whole-genome sequencing. This revealed 6 tumors with MYC or BCL2 rearrangements that were cryptic to breakapart FISH. Copy-number analysis identified 3 tumors with MYC and 6 tumors with MIR17HG gains or amplifications, both of which may contribute to dysregulation of MYC and its downstream pathways. Focal deletions of the PVT1 promoter were observed exclusively among DHITsig+ tumors lacking MYC translocations; this may also contribute to MYC overexpression. These results highlight that FISH fails to identify all HGBL-DH/THs, while revealing a range of other genetic mechanisms potentially underlying MYC dysregulation in DHITsig+ DLBCL, suggesting that gene expression profiling is more sensitive for identifying the biology underlying poor outcomes in GCB-DLBCL.

  Study EGAS00001004285

• Comprehensive Deep Sequencing Atlas in HCC tumors

  Establishment of a comprehensive deep sequencing atlas focused on Hepatocellular Carcinoma (HCC) tumors, employing Whole Genome Sequencing (WGS), RNA Sequencing (RNAseq), and Whole Exome Sequencing (WES). The atlas aims to unravel the intricate genetic landscape of HCC, providing a detailed characterization of genomic alterations, transcriptomic profiles, and key mutations associated with this liver cancer. The integration of WGS, RNAseq, and WES data offers a holistic perspective, facilitating a deeper understanding of the molecular mechanisms driving HCC pathogenesis. The resulting atlas serves as a valuable resource for researchers, clinicians, and the broader scientific community, contributing to advancements in HCC diagnostics, prognostics, and therapeutic interventions.

  Study EGAS00001007694

• Exome-sequencing identifies new oncogenes and tumor suppressor genes recurrently altered in hepatocellular carcinoma

  Hepatocellular carcinoma (HCC) is the most common primary liver malignancy. High-resolution copy number analysis of 125 tumors of which 24 were subjected to whole-exome sequencing identified 135 homozygous deletions and 994 somatic gene mutations with predicted functional consequences. We identified new recurrent alterations in 4 genes (ARID1A, RPS6KA3, NFE2L2 and IRF2) not previously described in HCC. Functional analyses demonstrated tumor suppressor properties for IRF2 whose inactivation, exclusively found in hepatitis B virus related tumors, leads to impaired TP53 function. Alternatively, inactivation of proteins involved in chromatin remodeling was frequent and predominant in alcohol related tumors. Moreover, activation of the oxidative stress metabolism and inactivation of RPS6KA3 were new pathways associated with WNT/beta-catenin activation, thereby suggesting a cooperative effect in tumorigenesis. This study shows the dramatic somatic genetic diversity in HCC, it reveals interactions between oncogene and tumor suppressor gene mutations markedly related to specific risk factors.

  Study EGAS00001000217

• Pre-neoplastic liver colonization by 11p15.5 altered mosaic cells in young children with hepatoblastoma

  In children, liver tumors are a heterogeneous group representing 1-2% of all cancers with the most common diagnosis being hepatoblastoma (HB). While HBs are predominantly sporadic, around 15% of cases develop as part of predisposition syndromes such as familial adenomatous polyposis (APC mutation) or Beckwith-Wiedemann (BWS; 11p15.5 locus altered). Here, we identified a mosaic genetic alteration of 11p15.5 locus in the liver in 17% of HB patients without a clinical diagnosis of BWS syndrome. These mosaic 11p15.5 alterations were never found in children with other types of liver tumor (hepatocellular carcinoma or adenoma, fibrolamellar carcinoma). Bulk transcriptomic analysis revealed the abundance of extracellular matrix, angiogenesis, and progenitor gene signatures in mosaic livers. In situ hybridization assay RNAscope allowed for the detection of 11p15.5 altered hepatocytes mosaicism in liver FFPE sections of HB patients presenting IGF2 overexpression and H19 downregulation together with an alteration of the zonal architecture of the liver. Spatial transcriptomics analysis revealed an overexpression of the IGF2 pathway, lipogenesis, and platelet activation in 11p15.5 altered hepatocytes. These data provide insights for 11p15.5 mosaicism detection as well as functional consequences of these alterations during the early steps of carcinogenesis.

  Study EGAS00001006692

• Genetics_and_Networks_of_Congenital_Heart_Defects

  Exome sequencing of families with Congenital Heart Defects of diverse sub-phenotypes. Comprises both parent-offspring trios for sporadic cases and multiplex families. Collaboration with David Brook, University of Nottingham. Funded by the British Heart Foundation.

  Study EGAS00001000762

• Whole genome and whole exome sequencing of serial biopsies of relapsed/refractory diffuse large B-cell lymphoma.

  Purpose: Diffuse large B-cell lymphoma (DLBCL) is cured in more than 60% of patients, but outcomes remain poor for patients experiencing disease progression or relapse (refractory or relapsed DLBCL [rrDLBCL]), particularly if these events occur early. Although previous studies examining cohorts of rrDLBCL have identified features that are enriched at relapse, few have directly compared serial biopsies to uncover biological and evolutionary dynamics driving rrDLBCL. Here, we sought to confirm the relationship between relapse timing and outcomes after second-line (immuno)chemotherapy and determine the evolutionary dynamics that underpin that relationship. Patients and methods: Outcomes were examined in a population-based cohort of 221 patients with DLBCL who experienced progression/relapse after frontline treatment and were treated with second-line (immuno)chemotherapy with an intention-to-treat with autologous stem-cell transplantation (ASCT). Serial DLBCL biopsies from a partially overlapping cohort of 129 patients underwent molecular characterization, including whole-genome or whole-exome sequencing in 73 patients. Results: Outcomes to second-line therapy and ASCT are superior for late relapse (>2 years postdiagnosis) versus primary refractory (<9 months) or early relapse (9-24 months). Diagnostic and relapse biopsies were mostly concordant for cell-of-origin classification and genetics-based subgroup. Despite this concordance, the number of mutations exclusive to each biopsy increased with time since diagnosis, and late relapses shared few mutations with their diagnostic counterpart, demonstrating a branching evolution pattern. In patients with highly divergent tumors, many of the same genes acquired new mutations independently in each tumor, suggesting that the earliest mutations in a shared precursor cell constrain tumor evolution toward the same genetics-based subgroups at both diagnosis and relapse. Conclusion: These results suggest that late relapses commonly represent genetically distinct and chemotherapy-naïve disease and have implications for optimal patient management.

  Study EGAS00001007053

• Deciphering Developmental Disorders (DDD)

  The Deciphering Developmental Disorders (DDD) study is a research collaboration between the Wellcome Trust Sanger Institute, the NHS clinical genetics services and families across the UK and Ireland. The project aims to improve the diagnosis of children with developmental disorders by using high-resolution microarray and massively parallel sequencing technologies on 12,000 children and their parents. Genetic changes that explain the child's symptoms will be displayed in the DECIPHER database (https://decipher.sanger.ac.uk). Extended datasets generated by the DDD project will be available in the European Genome-Phenome Archive with access carefully managed by a Data Access Committee.

  Study EGAS00001000775

• Histological Transformation and Progression in Follicular Lymphoma: a Clonal Evolution Study

  Background: Follicular lymphoma (FL) is an indolent, yet incurable B-cell malignancy. A subset of patients experience increased mortality rate driven by two distinct clinical end points: histological transformation and early progression after immuno-chemotherapy. The nature of tumor clonal dynamics leading to these clinical endpoints is poorly understood and previously determined genetic alterations do not explain the majority of transformed cases or accurately predict early progressive disease. We contend that detailed knowledge of the expansion patterns of specific cell populations plus their associated mutations would provide insight into therapeutic strategies and disease biology over the timecourse of FL clinical histories. Methods and Findings: Using a combination of whole genome sequencing, targeted deep sequencing and digital droplet PCR on matched diagnostic and relapse specimens, we deciphered the constituent clonal populations in n=15 transformation patients and n=6 progressors, and measured their change in abundance over time. We observed widely divergent patterns of clonal dynamics in transformed cases relative to progressed cases. Transformation specimens were generally composed of clones that were rare or absent in diagnostic specimens, consistent with dramatic clonal expansions that came to dominate the transformation specimen. This pattern was independent of time to transformation and treatment modality. By contrast, progression specimens were composed of clones that were already present in the diagnostic specimens and exhibited only moderate clonal dynamics, even in the presence of immuno-chemotherapy. Analysis of somatic mutations impacting 94 genes was undertaken in a validation cohort consisting of 395 samples from 277 patients in order to decipher disrupted biology in the two clinical endpoints. We found 12 genes were more commonly mutated in transformed samples than in preceding FL, including TP53, B2M, CCND3, GNA13, S1PR2 and P2RY8. Moreover, 10 genes were more commonly mutated in diagnostic specimens of early progressors including TP53, BTG1, MKI67 and XBP1. Conclusions: Our results illuminate contrasting modes of evolution shaping the clinical histories of transformation and progression. They have implication for interpretation of evolutionary dynamics in the context of treatment-induced selective pressures, and indicate that transformation and progression will require different clinical management strategies.

  Study EGAS00001001709

• Multi-focal genomic dissection of synchronous primary and metastatic tissue from de novo metastatic prostate cancer

  De novo metastatic prostate cancer is highly aggressive, but the paucity of routinely-collected tissue in this setting has hindered genomic stratification and jeopardizes precision oncology efforts. Here, we leveraged a rare study of surgical intervention in 43 de novo metastatic prostate cancers to assess somatic genotype across 607 synchronous primary and metastatic tissue foci plus circulating tumor DNA. Intra-prostate heterogeneity was pervasive and impacted clinically-relevant genes, resulting in frequent discordance between select primary-restricted foci and synchronous metastases. Additional complexity was driven in several instances by polyclonal metastatic seeding from the reservoir of phylogenetically-related primary populations. When simulating standard clinical practice relying on a single tissue focus, genomic heterogeneity plus highly variable per-sample tumor fraction caused false genotyping of dominant disease. However, in silico modeling demonstrated that analysis of multiple biopsy cores can rescue misassigned somatic genotypes. Our results define the relationship between synchronous treatment-naive primary and metastatic lesions in de novo metastatic prostate cancer and provide a framework for implementing genomics-guided patient management.

  Study EGAS00001006466

• The Precision Medicine in Liver Cancer across an Asia-pacific NETwork (PLANET)

  Hepatocellular carcinoma (HCC) is the 2nd most important cause of cancer deaths in the world. The outcomes of treatment in HCC are poor compared to other common cancers because there are no good systemic therapy drugs. We designed a prospective study that will involve 5 different sites within the established Asia-Pacific Hepatocellular Carcinoma Trials Group to study both the genetics as well as immune profiles of HCC in different ethnicities. In this study, patients will be followed-up and at recurrence the tissues to understand the evolution of disease progression. Here, we presented both the genomic (DNA) and phenotypic (RNA) evolution for the first batch of 56 patients. The detailed findings will be listed in the corresponding publication soon.

  Study EGAS00001003813

• Genetic landscape of pediatric ependymoma

  We performed whole-genome sequencing of 42 paired tumor/normal EPD genomes and analyzed somatically acquired single nucleotide variations (SNVs), insertion/deletions, structural variations and copy number variations in the cancer genomes

  Study EGAS00001000254

• This study aims to evaluate the relationship between cardiometabolic risk factors and the most common genetic variation (SNPs)

  Comprehensive data on lifestyle-related modifiable factors, sociodemographic, anthropometric, economic, biochemical, and genetic markers related to the occurrence of cardiometabolic diseases as part of the observational cross-sectional survey “2015 Health Survey of Sao Paulo with Focus on Nutrition (2015 ISA-Nutrition)”, a population-based study. Data of 805218 SNPs for 841 individuals was genotyped using the Axiom™ 2.0 Precision Medicine Research Array in the Thermo Fisher Scientific laboratory (Affymetrix Inc, Santa Clara, CA).

  Study EGAS00001007818

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__Colorectal

  he Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001003774

• Therapeutic Targeting of Ependymoma as Informed by Oncogenic Enhancer Profiling

  Genomic sequencing has driven precision-based oncology therapy; however, genetic drivers remain unknown or non-targetable for many malignancies, demanding alternative approaches to identify therapeutic leads. Ependymomas are chemotherapy-resistant brain tumours, which, despite genomic sequencing, lack effective molecular targets. Here, we mapped active chromatin landscapes in 42 primary ependymomas in two non-overlapping primary ependymoma cohorts. Enhancer regions revealed novel oncogenes, molecular targets, and pathways, which when subjected to small molecule inhibitor or shRNA treatment, increased survival and slowed proliferation in mouse and neurosphere patient-derived models of ependymomas. This study represents one of the largest enhancer mapping study of any cancer type to date, and provides a framework for target and drug discovery for other cancers recalcitrant to therapeutic development because of their lack of known genetic drivers.

  Study EGAS00001002696

• Genetic Effects on the Skin Methylome in Healthy Older Twins

  Study EGAS00001007816

• The subclonal architecture of metastatic breast cancer: Results from a prospective community-based rapid autopsy program 'CASCADE'

  Background: Understanding the cancer genome is seen as a key step in improving outcomes for cancer patients. Genomic assays are emerging as a possible avenue to personalised medicine in breast cancer. The majority of work in this area has targeted primary tumours however, and very few studies have performed comprehensive profiling of advanced disease. Evolution of the cancer genome during the natural history of breast cancer is largely unknown, as is the profile of disease at death. We sought to study in detail these aspects of advanced breast cancers that have resulted in lethal disease. Methods and Findings: Three patients with ER-positive, HER2-negative breast cancer and one patient with triple negative breast cancer underwent rapid autopsy as part of an institutional prospective community-based rapid autopsy program. Cases represented a range of management problems in breast cancer, including late relapse after early stage disease; de novo metastatic disease; discordant disease response and disease refractory to treatment. Between 5 and 12 metastatic sites were collected at autopsy together with available primary tumours and longitudinal metastatic biopsies taken during life. Samples underwent paired tumour-normal whole exome sequencing and single nucleotide polymorphism arrays. Subclonal architectures were inferred by jointly analysing all samples from each patient. Mutations were validated using high depth amplicon sequencing.Between cases, there were significant differences in mutational burden, driver mutations, mutational processes and copy number variation. Within each case, we found dramatic heterogeneity in subclonal structure from primary to metastatic disease and between metastatic sites, such that no single lesion captured the breadth of disease. Metastatic cross seeding was found in each case and treatment drove subclonal diversification. Subclones displayed parallel evolution of treatment resistance in some cases, and apparent augmentation of key oncogenic drivers as an alternative resistance mechanism. We also observed the key role of mutational processes in subclonal evolution.Limitations of this study include the potential for bias introduced by joint analysis of formalin fixed archival specimens with fresh specimens, and the difficulties in resolving subclones with whole exome sequencing. Other alterations that could define subclones such as structural variants or epigenetic modifications were not assessed. Conclusions: This study highlights the variety of mechanisms that shape the genome of metastatic breast cancer, and the value of studying advanced disease in detail. Treatment drives significant genomic heterogeneity in breast cancers which has implications for disease monitoring and treatment selection in the personalised medicine paradigm.

  Study EGAS00001002153

• Whole-exome sequencing of breast cancer metastasis and corresponding blood samples

  This study included samples from metastatic breast cancer patients who underwent a biopsy in the context of SAFIR01 (NCT01414933), SAFIR02 (NCT02299999), SHIVA (NCT01771458) and MOSCATO (NCT01566019) prospective trials. These French multicentre trials used high throughput genome analysis on fresh frozen tumor biopsies as a therapeutic decision tool for metastatic cancer patients, with solid cancers (SHIVA, MOSCATO) or specifically with breast cancer (SAFIR01, SAFIR02). All patients gave their informed consent for translational research and genetic analyses of their somatic DNA. Overall, whole-exome sequencing for a total of 216 pairs of metastatic tumor and unmutated DNA derived from corresponding blood samples was performed using Illumina technology. The results of the analysis of the mutational profile of metastatic breast cancer was reported in Lefebvre et al. (PMID:28027327).

  Study EGAS00001001695

• Submission 11 - study_title 1. Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industrys standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book

  Submission 11 - description 1. Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industrys standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book

  Study EGAS50000000426

• The Medical Genome Reference Bank: a whole genome data resource of 4,000 healthy elderly individuals.

  Allele frequency data from human reference populations is of increasing value for filtering and assignment of pathogenicity to genetic variants. Aged and healthy populations are more likely to be selectively depleted of pathogenic alleles, and therefore particularly suitable as a reference populations for the major diseases of clinical and public health importance. However, reference studies of the healthy elderly have remained under represented in human genetics. We have developed the Medical Genome Reference Bank (MGRB), a large scale comprehensive whole genome dataset of confirmed healthy elderly individuals, to provide a publicly accessible resource for health related research, and for clinical genetics. It also represents a useful resource for studying the genetics of healthy aging. The MGRB comprises 4,000 healthy, older individuals with no reported history of cancer, cardiovascular disease or dementia, recruited from two Australian community based cohorts. DNA derived from blood samples will be subject to whole genome sequencing. The MGRB will measure genome wide genetic variation in 4,000 individuals, mostly of European decent, aged 60 to 95 years (mean age 75 years). The MGRB has committed to a policy of data sharing, employing a hierarchical data management system to maintain participant privacy and confidentiality, whilst maximizing research and clinical usage of the database. The MGRB will represent a dataset of international significance, broadly accessible to the clinical and genetic research community.

  Study EGAS00001003511

• Comprehensive molecular profiling identifies novel genetic drivers and subtypes underlying medulloblastoma

  Current therapies for medulloblastoma (MB), a highly malignant childhood brain tumor, impose debilitating effects on the developing child, warranting the development of molecularly targeted treatments with reduced toxicities. Prior studies have failed to disclose the full spectrum of driver genes and molecular processes operative in MB or adequately explain heterogeneity among molecular subgroups. Herein, we detail the somatic landscape across 491 sequenced MBs and molecular heterogeneity amongst 1,256 epigenetically analyzed cases, identifying subgroup-specific mutational signatures, driver genes, and pathway alterations including previously unappreciated actionable therapeutic targets. Integrative approaches for assigning driver genes to subgroups explained >65-70% of Group 3 and Group 4, doubling previous knowledge. Novel subtypes underlying Group 3 and Group 4 were differentially enriched for specific driver events, including hotspot in-frame indels targeting KBTBD4 and ‘enhancer hijacking’ driving activation of PRDM6. Thus, application of integrative genomics to an unprecedented cohort of clinical samples derived from a single childhood cancer entity has disclosed a series of new cancer genes and biologically relevant subtype diversity that represent attractive therapeutic targets for treating MB.

  Study EGAS00001001953

• The Proteogenomic Subtypes of Acute Myeloid Leukemia

  Acute myeloid leukemia (AML) is an aggressive blood cancer with poor prognosis. We report a comprehensive proteogenomic analysis of bone-marrow biopsies from 252 uniformly treated AML patients to elucidate the molecular pathophysiology of AML in order to inform future diagnostic and therapeutic approaches. In addition to in-depth quantitative proteomics, our analysis includes cytogenetic profiling and DNA/RNA sequencing. We identify five proteomic AML subtypes, each reflecting specific biological features spanning genomic boundaries. Two of these proteomic subtypes correlate with patient outcome, but none are exclusively associated with specific genomic aberrations. Remarkably, one subtype (Mito-AML), which is only captured in the proteome, is characterized by high expression of mitochondrial proteins and confers poor outcome, with reduced remission rate and shorter overall survival upon treatment with intensive induction chemotherapy. Functional analyses reveal that Mito-AML is metabolically wired towards stronger complex I dependent respiration and is more responsive to treatment with the BCL2 inhibitor venetoclax.

  Study EGAS00001005950

• Genomic landscape and PD-1 blockade in Natural-killer/T cell lymphoma

  Natural killer/T-cell lymphoma (NKTL) is an aggressive malignancy with a predilection for Asian, Mexican and South American populations. With the exception of Japan, it is the most common mature T-cell lymphoma in Asia. NKTL presents as extranodal disease and mostly affects the upper aerodigestive tract. Neoplastic cells are invariably infected by the Epstein-Barr virus (EBV) and characterized by a cytotoxic phenotype. The genetic landscape of NKTL has been recently unraveled by discoveries describing recurring mutations altering the JAK-STAT pathway, epigenetic modifiers, the DDX3X gene and genetic predisposition in the HLA-DPB1 gene.The genomic landscape of NKTL has been interrogated by whole-exome sequencing, targeted sequencing and single nucleotide polymorphism arrays, but has yet been studied with whole-genome sequencing (WGS). In this study, we will use a combination of WGS, targeted-capture sequencing (TCS) and RNA sequencing data to explore the genetic landscape and its relevance to immunotherapy in NKTL

  Study EGAS00001003828

• Detection of clinically relevant genetic and transcriptomic landscape in DLBCL uniformly treated by R-CHOP

  Recent studies using next-generation sequencing strategies have described the landscape of genetic alterations in diffuse large B-cell lymphoma (DLBCL). However, little is known about the clinical relevance of recurrent mutations and copy number alterations and their transcriptional footprints. This study examines the frequency, interaction and clinical impact of recurrent genetic aberrations in DLBCL using high-resolution technologies in a large population-based cohort.

  Study EGAS00001002657

• Pediatric Low-Grade Glioma RNA and Targeted Sequencing

  Pediatric low-grade gliomas (pLGG) are frequently driven by genetic alterations in the RAS/MAPK pathway yet show unexplained variability in their clinical outcome. To address this, we characterized a cohort of >1,000 clinically annotated pLGG. 84% of cases harbored a driver alteration, while those without an identified alteration also often exhibited up-regulation of the RAS/MAPK pathway. pLGG could be broadly classified based on their alteration type. Rearrangement-driven tumors were diagnosed at a younger age, enriched for WHO grade I histology, infrequently progressed, and rarely resulted in death as compared to SNV-driven tumors. Further sub-classification of clinical-molecular correlates stratified pLGG into risk categories. These data highlight the biological and clinical differences between pLGG subtypes and opens avenues for future treatment refinement.

  Study EGAS00001004242

• How to use the EGA search box

  Tips on how to search Tip 1: Use simple and clear keywords No matter what you are searching: a study, a dataset or a committee; the search will look recursively in all the fields of all the entities in the database. Thus, there is no need to specify which type of data you are looking for. Try to use single and specific words and avoid long and complex expressions. Try it out: cancer rna-seq instead of cancer studies using RNA-seq. Tip 2: Narrow your results using search operators Search operators give you more control over the results. They manage the way keywords are used to restrict the search. By default, the search engine applies an AND operator when a space is inserted between two words. Include OR (capitalised) between the keywords in your search in order to show pages containing either term or both terms. Try it out: Search all the studies based on transcriptomic data, including those ones that use RNA sequencing to obtain this data. Tip 3: Do not worry about details The search engine automatically checks for the most common spelling mistakes of given words and suggests the use of the correct version. It also ignores capital letters and most punctuation so none of these mistakes will hamper the accuracy of your search. Besides, when using a combination of words, the search engine will suggest similar combinations with a higher number of results. Tip 4: Use words that are likely to appear within the text Unfortunately, our search engine is not able to interpret words yet. Therefore, words which do not appear in the body text will not return any result despite them denoting a group of present terms. For instance, if we are looking for studies focused on neurological diseases, using neurological as a keyword would not be the best option. Instead, you should use the name of each neurological disease such as bipolar disorder, schizophrenia or depression. In the same fashion, incomplete words do not return any result. Please include an asterisk (*) before and/or after the incomplete word in order to allow for partial matching. Try it out: canc* instead of canc(without wildcard). Also you can try out *oma, or even *geneti* Tip 5: Narrow down your search by filtering the results You can filter the results by the following options: general, study, and dataset. Under these categories, you will find more sub-filters to refine your search. Make sure that you click on Apply in order to filter the results. You can clear the filtering anytime. Advanced Searches Additional example queries: Search for DUO:0000005 and word lung example query Or write: DUO:0000005 AND lung Search for an exome sequencing study in dbGaP example query Or write: study_type: "exome sequencing" AND repository:dbGaP Search for an exome sequencing study in EGA example query Or write: study_type: "exome sequencing" AND repository:ega Search for a dataset that is at the EGA beacon and with type "Whole genome sequencing" and with number of samples between 100 and 2000 and with technology "Illumina HiSeq 2000" example query Or write: is_in_beacon:true AND dataset_types:"Whole genome sequencing" AND samples:[100 TO 2000] AND dataset_technologies:"Illumina HiSeq 2000" Search for PMIDS example query Or write: pmids:32025007

  Documentation discovery/metadata/search-box

• What is a DAC?

  What is a DAC? Given the complexity, scale, and diversity of global submitters and studies, the EGA operates a distributed data access model in which requests are made to the data controller, not to the EGA. The European Commission defines a data controller, in the General Data Protection Regulation (GDPR), as the person that determines the purposes for which and the means by which personal data is processed. A Data Access Committees, commonly referred to as DACs, comprise on or more individuals (or data controllers) that review data access requests and make decisions on who can access personally identifiable genetic, phenotypic, and clinical data deposited at the EGA. Therefore, the members of a DAC should be individuals who have the authority to approve data access requests. The animation describes how you can authorise access to your sensitive data with the help of Data Access Committee and Authorisation tool. Acknowledgement to CSC - IT Center for Finland, Elixir Finland, Elixir Europe. Frequently Asked Questions How can I create a Data Access Committee? How can I create a Data Access Committee? The members of a DAC can come from different areas of expertise, such as data management, data analysis, information technology, legal and compliance, subject matter experts, privacy and security, and representatives from the organisations or individuals that provide data to the DAC. The specific members of a DAC can vary depending on the needs of the organisation and the type of data being managed. The EGA strongly suggests checking with your organisation to align with its regulations How should a DAC be named? The chosen name must be informative to the applicant.  For example, internal identifiers, such as grant numbers, should not be used. Individual PI names should also not be used. DAC's are often named after the organisation or department of the data source.  Browse the full list of DAC names currently in the EGA. How can I become an EGA DAC contact? To register a DAC at the EGA you must create first as an EGA user. Once your EGA user has been approved by the Helpdesk team, you will be able to log in to the DAC Portal. How can I register a DAC? To register a DAC, follow the DAC Portal instructions.  You will be required to provide a DAC name, name of the individual(s) that make up your DAC and contact details for your DAC including your Institutional email(s). Wherever possible, the DAC should make sure that all points of contact are readily available and able to answer any initial data requests/queries in < 2 weeks.  Once your DAC is registered, you will have to wait upon the validation from our Helpdesk team. As soon as all the validations have been completed, your DAC will be activated. Alternatively, you can also establish a DAC at the EGA during a programmatic submission through Webin API. Which are the possible roles of a DAC contact? There are two possible roles for DAC contacts: member and admin. An admin has additional privileges compared to a member: An “admin” can manage data requests, create and edit policies, edit the content of the DAC, add or remove contacts, and decide the role of each contact. A “member” can manage data requests and create policies. However, a member does not have permission to modify DAC details, edit information from policies where they are not admins, or add/remove contacts. There is no limit to the number of admins in a DAC, and each admin is responsible for deciding who should have editing privileges. This allows for a more decentralised and democratic approach to managing the DAC. How can I modify the information of a DAC? To modify a DAC, follow the instructions here. Keep in mind that only DAC contact with an admin role can modify the information of a DAC. If your DAC was registered before the lauch of the DAC Portal, and its ID is EGAC0 (not EGAC5), you must use the programmatic submission to modify it. Please, do not hesitate to contact our Helpdesk team if you need help with this! To prevent potential data breaches and ensure adherence to GDPR regulations, it is essential that the European Genome-Phenome Archive (EGA) is informed via the Helpdesk team of any changes to the Data Access Committee (DAC). This should be done in addition to any changes being made on the DAC portal. Data Controllers (as per the definition in the DPA) are also responsible for notifying the previous DAC of any modifications. Without proper notification, changes might not be automatically updated in our system, leading to the risk of incorrect permissions being applied and potential data access issues. Therefore, it is imperative that all Data Controllers follow this protocol to maintain data integrity and security. What’s the link between DAC, policy and dataset? A dataset is linked to one single policy. At the same time, one policy has a one to one relationship with a DAC. In this example, you can see that in this dataset page, we are only showing the information of one DAC (1 dataset - 1 DAC). However, the ratio of objects does not work the same in the other direction. One DAC can own multiple policy objects. And each policy object can be reused in several datasets. Thus, one DAC can manage one or more datasets. In this example, you can see that in this DAC page, we are showing all the datasets that are managed by one DAC (1 DAC - >400 datasets). EGA Data Access Committee Best Practices Which are the EGA DAC best practices? Refer to DAC Best Practices What happens if a DAC member changes institutions? EGA is committed to the protection and ownership of the data stored in our systems. We respect the institution's ownership of the data, and as such, if a DAC member changes institutions, the ownership of the data will not be transferred to the new institution. Therefore, before changing institutions, we request that the DAC contact add a new member who will replace them once they no longer work at the institution. This ensures that the data remains protected and is accessible to authorised personnel at the institution. To prevent potential data breaches and ensure adherence to GDPR regulations, it is essential that the European Genome-Phenome Archive (EGA) is informed via the Helpdesk team of any changes to the Data Access Committee (DAC). This should be done in addition to any changes being made on the DAC portal. Data Controllers (as per the definition in the DPA) are also responsible for notifying the previous DAC of any modifications. Without proper notification, changes might not be automatically updated in our system, leading to the risk of incorrect permissions being applied and potential data access issues. Therefore, it is imperative that all Data Controllers follow this protocol to maintain data integrity and security. What happens if EGA detects an unresponsive DAC? EGA defines an unresponsive DAC as a DAC with one or more contacts who do not respond to data access requests. EGA has procedures in place to identify these types of DACs, escalate the issue, and attempt to reassign the DAC to a responsive contact. This is a crucial step in ensuring that data can be accessed and utilised by researchers. If EGA identifies an unresponsive DAC, the organisation will first try to resolve the issue by escalating it to the appropriate parties. This may involve attempting to reassign the DAC to a more responsive contact. Unfortunately, in situations where we cannot reassign the DAC, the dataset will be withdrawn from the public website and the files will be removed from our system. If an EGA ID is referenced in a publication, the EGA will take extra steps to ensure that the public is made aware of the data's unavailability. I don't want to receive an email notification for pending requests. How can I do that? If you are an EGA DAC with pending requests, you will always receive emails for new data access requests. However, the EGA understands that a request resolution can take some time, for this reason, if you add a comment (make sure you save it by clicking the APPLY button!) we will filter those requests at the time of sending the notification! How can I manage data access requests? What documentation does the DAC need to provide? Each dataset that is submitted to the EGA must be linked to a policy object. The policy is a Data Access Agreement (DAA), which defines the terms and conditions of using the dataset, such as how the data files should be stored once downloaded or details of publication embargoes that should be observed by the approved user. As part of the Data Access Agreement, information regarding the application can be captured to help inform the DAC when making its decision. For example, requestors could be asked to provide a proposed title for their research and a proposal of how the data will be used. By asking for provision of such information the DAC can be assured that the requestor fully understands any consents associated with the data. It is important that accounts created at the EGA, are created solely for those individuals that will be downloading the data from the EGA. As part of the data access request, we strongly encourage you to identify individuals that will need an account at the EGA in order to prevent sharing of login details, which is strictly prohibited under EGA user account policy. Such information can easily be captured in the DAA. NOTICE The data access agreement template below is provided for guidance only and should be adapted as you see fit to suit your own purpose. In the interest of promoting data sharing, we suggest that if an agreement cannot be met around clause 19 in this example that both parties should agree to remain silent, and that the clause should be removed from the agreement. Example DAA How can the DAC provide the DAA? The DAC should provide their own DAA when registering a policy. Data requestors will download this document and should fill it in and send it back to the DAC. Data access decisions should be based on such documentation. The DAA can be downloaded through the request data webpage. Once it has been filled in, the signed copy of the DAA can be uploaded back to the request data webpage and sent to the DAC for review. How can I grant access to the data? Once you receive a data access request, you can login to the DAC Portal. In this portal you will see all your pending requests and will be able to grant or decline access to the requestors. I am a member of the Data Access Committee. Could I approve somebody else to deal with the requests on my behalf? If you want to delegate data access decisions to someone else, make sure that the individual's account is officially registered as a member of the DAC. Remember that a DAC contact with an "admin" role can always add new members to an existing DAC, remove members, and modify contact details through the DAC Portal. Can I automatise the process of managing data access requests? The answer is yes! You can use a programmatic approach using our DAC API! Check out the DAC API specification! Data Breach What should a DAC do if they suspect a breach? If a DAC suspects a data breach of one or more of their datasets, they should immediately contact the EGA Helpdesk team at this link. The DAC must provide the following information when contacting the EGA Helpdesk team: A list of affected datasets An estimated date of the data breach (or interval of dates) A list of unauthorised users who accessed the data (if available). Otherwise, they can provide a list of authorised users for the affected datasets Any observations they would like to raise to the EGA team Once the DAC has contacted the EGA team, we will respond within 48 hours (please allow some leeway during peak times) and activate our data breach protocol. What can I expect from the EGA if they detect a breach? Once the EGA determines that a security incident has occurred, we will notify all DAC members that a data breach has been detected, and take steps to contain the incident. Containment approaches may include: Revoking a data provider's access to the EGA resources, such as by changing passwords. Removing affected EGA datasets from distribution, such as by withdrawing a dataset. Disabling certain functions or services, such as the EGA ingestion pipeline. Shutting down the system or disconnecting it from the network. After the incident has been contained, the EGA will determine whether it is necessary to eradicate components related to the incident. Finally, the EGA will enable recovery of the service to normal operation and confirm that all services are functioning normally.

  Documentation access/data-access-committee/what-is-dac

• Data Use Ontology (DUO)

  Data Use Ontology Data Use Ontology at EGA The EGA is committed to its involvement in the work of GA4GH. In an effort to enhance data discoverability and streamline data access, EGA have implemented the use of the Data Use Ontology (DUO), based on consent codes as described in Dyke et al. 2017. The Data Use Ontology codes will be displayed on the live dataset page of your submission to advise any would be requestor on how the data can be used and also to enhance data discoverability as users will be able to search on these codes to find applicable datasets. DUO can be browsed online via the Ontology Lookup Service Learn more reading the Data Use Ontology publication and the GA4GH Machine-Readable Consent Guidance! Check our DAC Portal Take The Tour and learn how to add DUO codes to your policy! Term Shorthand Label Description DUO:0000004 NRES no restriction This data use permission indicates there is no restriction on use. DUO:0000042 GRU general research use This data use permission indicates that use is allowed for general research use for any research purpose. DUO:0000006 HMB health or medical or biomedical research This data use permission indicates that use is allowed for health/medical/biomedical purposes; does not include the study of population origins or ancestry. DUO:0000007 DS disease specific research This data use permission indicates that use is allowed provided it is related to the specified disease. DUO:0000011 POA population origins or ancestry research only This data use permission indicates that use of the data is limited to the study of population origins or ancestry. DUO:0000012 RS research specific restrictions This data use modifier indicates that use is limited to studies of a certain research type. DUO:0000015 NMDS no general methods research This data use modifier indicates that use does not allow methods development research (e.g., development of software or algorithms). DUO:0000016 GSO genetic studies only This data use modifier indicates that use is limited to genetic studies only (i.e., studies that include genotype research alone or both genotype and phenotype research, but not phenotype research exclusively) DUO:0000018 NPUNCU not for profit, non commercial use only This data use modifier indicates that use of the data is limited to not-for-profit organizations and not-for-profit use, non-commercial use. DUO:0000019 PUB publication required This data use modifier indicates that requestor agrees to make results of studies using the data available to the larger scientific community. DUO:0000020 COL collaboration required This data use modifier indicates that the requestor must agree to collaboration with the primary study investigator(s). DUO:0000021 IRB ethics approval required This data use modifier indicates that the requestor must provide documentation of local IRB/ERB approval. DUO:0000022 GS geographical restriction This data use modifier indicates that use is limited to within a specific geographic region. DUO:0000024 MOR publication moratorium This data use modifier indicates that requestor agrees not to publish results of studies until a specific date. DUO:0000025 TS time limit on use This data use modifier indicates that use is approved for a specific number of months. DUO:0000026 US user specific restriction This data use modifier indicates that use is limited to use by approved users. DUO:0000027 PS project specific restriction This data use modifier indicates that use is limited to use within an approved project. DUO:0000028 IS institution specific restriction This data use modifier indicates that use is limited to use within an approved institution. DUO:0000029 RTN return to database or resource This data use modifier indicates that the requestor must return derived/enriched data to the database/resource. DUO:0000043 CC clinical care use This data use modifier indicates that use is allowed for clinical use and care. DUO:0000044 NPOA population origins or ancestry research prohibited This data use modifier indicates use for purposes of population, origin, or ancestry research is prohibited. DUO:0000045 NPU not for profit organisation use only This data use modifier indicates that use of the data is limited to not-for-profit organisations. DUO:0000046 NCU non-commercial use only This data use modifier indicates that use of the data is limited to not-for-profit use. Point to Notice: For the consent code DUO:0000007 where data is restricted to use on a specific disease, please accompany it with an appropriate ontology from MONDO e.g., If the data is restricted to the use of research into juvenile idiopathic arthritis the code should be displayed as DUO:0000007; MONDO:0011429.

  Documentation access/data-access-committee/data-use-ontology

• How to request data

  Request Data Access If you're looking to access data from the EGA for your research, you are in the right documentation page! In this page you will find a step by step guide on how to request data archived at the EGA, as well as some frequently asked questions you might find useful. When requesting data, you'll need to provide information about your research project and intended use of the data. Keep in mind that your data access request may require additional approvals or agreements depending on the datasets and data providers involved. Step by step guide Register yourself as an EGA user. Validate your account. A validation link will be sent to your email to activate your EGA user account. Log into the EGA page. Search the dataset of interest from the dataset catalogue or search bar. Click on "Request access" Add a comment requesting these files and send your request Your request is successfully registered, and the DAC will receive a notification about your request In addition to submitting your request, you should also contact the DAC directly via e-mail. You can access the DAC's contact information from the relevant dataset page. Frequently Asked Questions (FAQ) Which is the role of the EGA in the data access process? The European Genome-phenome Archive (EGA) facilitates the secure distribution under controlled access of personally identifiable genetic and phenotypic data. Data Access Committee (DAC) is a body of one or more individuals who are responsible for data release to external requestors, based on participant consent and/or National Research Ethics terms. How do I request access to multiple datasets? To request access for multiple datasets managed by the same Data Access Committee (DAC), please start by visiting the DAC catalogue to locate the DAC of your choice. Once you've found the relevant DAC, proceed to its dedicated page where you'll find a "Request access" button. After logging in to the EGA website, you'll be presented with a comprehensive list of datasets under the chosen DAC. Select the datasets you're interested in, and then compose a message indicating your access request. Click the "Send" button to submit your request, which will include the chosen datasets. Please be sure to review the data usage policies for the requested datasets, as policies can vary among datasets managed by the same DAC. I am a co-applicant. Will I be given a joint access account? Each applicant needs to create an EGA account themselves, with unique login details. User log-in details are for individual use only and should never be shared, under any circumstances. EGA services are only provided to EGA account holders. Therefore, the co-applicant will send a formal request to the DAC. What happens if a co-applicant leaves or a new member needs to be added to an existing DAC application? The appropriate Data Access Committee (DAC) should be contacted and informed about the required changes so that the application can be updated. I have changed my place of work since my EGA account was created. Can I still have access to data? You must contact the relevant Data Access Committee (DAC). The DAC did not reply to my data access request. How should I proceed? There is no estimated time for DAC response. Please allow up to four weeks for a response. In the meantime, please send them a weekly reminder of the status of your request by emailing them directly.If the DAC becomes unresponsive, meaning that they fail to communicate with a requestor within the specified time frame, please contact the EGA Helpdesk team. I have an account with the EGA and would like access to further datasets. How should I proceed? You need to reapply to the relevant Data Access Committee (DAC). Once the DAC has approved your application your account will be updated and an email will be sent to notify you of a change made to your account. How do I download files of the datasets I have been granted access to? The preferred method for data download and decryption is the EGA Secure Download Client. Please carefully review the provided documentation. How do I download metadata? Metadata is retrieved from the EGA webpage; you will not need to use any download client. Be informed that you will only be able to download metadata of your approved datasets. For such download, you should first log in the EGA webpage with your credentials. Then browse the metadata's dataset you have gained access and you will find a metadata download button. You may also want to have a look our metadata schema. I have forgotten or misplaced my user account password; how do I get a new one? Click on "Log in", located in the top right corner of the EGA homepage. Then click "Forgot password", type in your registered institutional email address, and instructions for resetting your password will be sent to you. Please check both regular and junk/spam folders. I was sent a link to set a password for my download account, but it seems like the link has expired. What should I do? The procedure is the same as the one for a forgotten password, explained in the previous question.

  Documentation access/request-data/how-to-request-data

• Projects

  Projects Jointly managed by the European Bioinformatics Institute (EMBL-EBI) in Cambridge (UK) and the Centre for Genomic Regulation (CRG) in Barcelona, the EGA provides an invaluable service to the worldwide biomedical research community. The teams leading the EGA are involved in several international partnerships and consortia in numerous scientific fields, where they contribute to ambitious projects. In addition to the project listed below, the EGA is in a long-standing partnership with the Global Alliance for Genomics and Health (GA4GH), as described on the dedicated page. On-going projects Project Duration Domain Funder Tags SCAILED | SCAILED (SCale-up Biotech AI Innovation by Leveraging Responsible Data Use under the European Health Data Space) aims to accelerate the development and deployment of Artificial Intelligence (AI) and digital solutions in the European biotech sector by harnessing high-quality health data within the secure, interoperable framework of the European Health Data Space (EHDS). 2026-2029 AI solutions; EHDS EU4Health Programme ACCESS DOCUMENTATION INFRASTRUCTURE CANDLE | CANDLE project aims to conceptualise and advance the development of National Cancer Data Nodes (NCDNs) in European countries. These NCDNs will boost the reuse of cancer data for research, innovation and policy making, in order to improve diagnostics and treatment for cancer patients, as well as prevention and early detection. 2025-2028 Cancer Horizon Europe DOCUMENTATION EASIGEN-DS | The EASIGEN-DS project aims to conduct a design study to establish a new European Research Infrastructure on Advanced Genomics Technologies, EASIGEN. To develop an excellent scientific, technological and operational design, we will conduct landscape studies, stakeholder consultations, and community surveying. 2025-2028 Genomic and health data Horizon Europe DATA MANAGEMENT DOCUMENTATION INFRASTRUCTURE Go-IMPaCT | Go-IMPaCT will contribute sequenced genomes and provide infrastructure as part of IMPaCT-Cohort, one of the three fundamental pillars of the Precision Medicine Infrastructure associated with Science and Technology (IMPaCT) program in Spain. Along with the Genome of Europe (GoE) project, around 18.000 people will have their genomes sequenced, also contributing to Spain's commitments in 1+MG. Go-IMPaCT will fund the development of an EGA node to manage and share this genomic and phenoclinic data, laying the foundations for regional and ethnic genomic variability in Spain to be available for research purposes. The IMPaCT cohort is created with the spirit of being an open research tool, compatible with the rest of the health research ecosystem, and other international initiatives. 2025-2027 Large-scale genomics and health data; personalised medicine Instituto de Salud Carlos III ACCESS DISCOVERY INFRASTRUCTURE METADATA STANDARDS FAIR-FEGA | This project seeks to accelerate data depositions into FEGA, significantly increasing the data flow in and from FEGA nodes. It will build capacity within the FEGA nodes and increase awareness in a wide range of stakeholders, thus altogether achieving the ultimate goal of enhancing data reuse. The project will be carried out by a strategic consortium comprising seven ELIXIR nodes and two ELIXIR communities. 2025-2026 Not applicable ELIXIR ACCESS DISCOVERY DOCUMENTATION INFRASTRUCTURE METADATA STANDARDS FEGA-Connect | A consortium of six ELIXIR nodes plus the Polish FEGA node (in-kind contribution) joining forces to build a solid base to develop solutions for effective multi-omic sensitive data integration between FEGA nodes and other infrastructures and specialised Data repositories. We aim to promote a more coherent data deposition, discoverability and retrieval of multi-omics datasets, providing FAIRer data and consequently accelerating research. 2025-2026 Multi-omics data ELIXIR ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE METADATA STANDARDS IMPaCT-Data 2 | IMPaCT-Data 2 will develop a digital platform for the integration and modelling of biomedical data associated with IMPaCT (Precision Medicine Infrastructure associated with Science and Technology) projects in Spain. It will deploy a sustainable infrastructure that facilitates the integration, standardisation, interoperability and analysis of clinical, genomic, molecular and medical imaging data. This platform will be aligned with European projects such as Genome of Europe (GoE), the first project to make use of the European Genomic Data Infrastructure (GDI), and EUCAIM. IMPaCT-Data 2 will benefit from advanced Artificial Intelligence and High Computing Capacity Systems capabilities, offering robust and accessible tools for researchers from the National Health System in Spain. 2025-2026 Large-scale genomics and health data; personalised medicine Instituto de Salud Carlos III ACCESS DISCOVERY INFRASTRUCTURE METADATA STANDARDS SenSec | This project aims to establish a mechanism for orchestrating secure access to sensitive data hosted by the EGA, whether in Central EGA or any Federated Node, from Galaxy, a popular open-source, community-driven VRE (Virtual Research Environment) for bioinformatics analysis. Building on a previous prototype that enabled Galaxy users within Trusted Research Environments (TREs) to decrypt sensitive data for workflow execution without sharing private encryption keys, SenSec will expand this prototype into a comprehensive solution for secure data analysis in Galaxy, facilitating encrypted data access and transfer from FEGA/EGA repositories to designated TREs. 2025-2026 Genomic and health data; trusted research environment ELIXIR ACCESS DATA ANALYSIS ERDERA | The European Rare Disease Research Alliance (ERDERA) takes over EJPRD to deliver concrete health benefits to rare disease patients in the next decade by advancing prevention, diagnosis and treatment research. To leave no one behind, over 170 organisations championed by the European Union and member states are working hand in hand to make Europe a world leader in rare diseases research and innovation. 2024-2034 Rare diseases Horizon Europe; "La Caixa" Foundation cofunds CRG's contribution ACCESS DATA ANALYSIS DISCOVERY INFRASTRUCTURE SYNTHIA | The aim of SYNTHIA is to deliver validated, reliable tools and methods for synthetic data generation (SDG). The tools will cover multiple data types including lab results, clinical notes, genomics, imaging and m-health data. SYNTHIA also hopes to make possible the generation of longitudinal data. 2024-2029 Genomic and health data; multi-omics; AI solutions Innovative Health Initiative (IHI) DATA ANALYSIS DATA MANAGEMENT INFRASTRUCTURE GoE | The Genome of Europe initiative aims to build a European network of national genomic reference cohorts of at least 500.000 citizens. These reference cohorts will be selected to be representative of the European population. 2024-2028 Large-scale genomic and health data Horizon Europe ACCESS DISCOVERY INFRASTRUCTURE METADATA STANDARDS HEREDITARY | HEREDITARY aims to transform the way we approach disease detection, prepare treatment response, and explore medical knowledge by building a robust, interoperable, trustworthy, and secure framework that integrates multimodal health data (including genetic data) while ensuring compliance with cross-national privacy-preserving policies. 2024-2027 Neurodegenerative disorders, gut-brain interplay Horizon Europe DATA MANAGEMENT DATA ANALYSIS EOSC-ENTRUST | The mission of EOSC-ENTRUST is to create a European network of trusted research environments for sensitive data and to drive European interoperability by joint development of a common blueprint for federated data access and analysis. 2024-2026 Trusted Research Environment Horizon Europe INFRASTRUCTURE EBV-MS | "Targeting Epstein-Barr Virus Infection for Treatment and Prevention of Multiple Sclerosis". The ambitious goals of the project are to answer the questions why only a few EBV infected persons develop MS, and define the underlying mechanism of this process, as well as clarify if targeting the EBV infection can prevent MS or improve the disease course. 2023-2028 Viral-host genetics; immune response; disease modelling; disease prevention; AI/ML solutions Horizon Europe DATA MANAGEMENT DATA ANALYSIS WISDOM | WELL-BEING IMPROVEMENT THROUGH THE INTEGRATION OF HEALTHCARE AND RESEARCH DATA AND MODELS WITHOUT BORDER FOR CHRONIC IMMUNE-MEDIATED DISEASES aims to deploy novel approaches for data processing, harmonisation, management, and secure data sharing and federated access for diseases like multiple sclerosis. Using an end-user guided approach, it will facilitate responsible and critical assessment of the use of AI in healthcare. 2023-2028 Chronic immune-mediated diseases Horizon Europe DATA MANAGEMENT INFRASTRUCTURE EUCAIM | EUropean Federation for CAncer IMages is a project that will build a highly secure, federated and large-scale European cancer imaging platform, with capabilities that will greatly enhance the potential of Artificial Intelligence in oncology. 2023-2027 Cancer Digital Europe Programme (DIGITAL) DISCOVERY CONTAGIO | CONTAGIO (COhorts Network To be Activated Globally In Outbreaks) aims to create coordination mechanisms to rapidly react to infectious disease (re-)emergence in low- and middle-income countries (LMICs). 2023-2026 Infectious Diseases European Commission - Horizon Europe ACCESS DATA MANAGEMENT DISCOVERY Youth-GEMs | Youth-GEMS (Gene Environment Interactions in Mental Health TrajectorieS of Youth) will conduct research into the genetic and environmental factors of mental health in young European people. 2022-2027 Mental health European Commission - Horizon Europe DATA MANAGEMENT DISCOVERY GDI | The European Genomics Data Infrastructure project is enabling access to genomic and related phenotypic and clinical data across Europe. It is doing this by establishing a federated, sustainable and secure infrastructure to access the data. 2022-2026 Genomic and health data European Commission - Horizon Europe; "La Caixa" Foundation cofunds CRG's contribution DISCOVERY DOCUMENTATION INFRASTRUCTURE IMPaCT-T2D | The IMPaCT-T2D project aims at studying the complete genomes of a large cohort of patients with Type 2 Diabetes mellitus (T2D), using modern sequencing technologies and artificial intelligence (AI) in order to improve the stratification and pharmacological treatment in the context of precision medicine. 2022-2025 Cardiovascular and Complex Diseases Spanish Ministry of Science and Innovation; Instituto de Salud Carlos III ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE Completed projects Project Duration Domain Funder Tags EOSC4Cancer | EOSC4Cancer builds on existing projects, research outcomes and established community solutions to create the federated FAIR data, analysis and services infrastructure needed for European Cancer research programmes. 2022-2025 Cancer European Commission - Horizon Europe DISCOVERY EuCanImage | A European Cancer Image Platform Linked to Biological and Health Data for Next-Generation Artificial Intelligence and Precision Medicine in Oncology. 2020-2025 AI Solutions in Oncology European Commission - H2020 Programme; "La Caixa" Foundation cofunds CRG's contribution DATA MANAGEMENT METADATA STANDARDS GenoMed4ALL | A consortium built to empower personalised medicine in the field of haematological diseases through the use of AI and the pooling of genomic and clinical data. 2020-2025 Hematological diseases European Commission - H2020 Programme DISCOVERY METADATA STANDARDS BY-COVID | The BeYond-COVID project aims to make COVID-19 data accessible to scientists in laboratories but also to anyone who can use it, such as medical staff in hospitals or government officials. Going beyond SARS-CoV-2 data, the project will provide a framework for making data from other infectious diseases open and accessible to everyone. 2021-2024 Infectious diseases European Commission - H2020 Programme ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE IMPaCT-Data | IMPaCT-Data aims to create the infrastructure for secondary use of data from Spanish healthcare systems - electronic health records, medical imaging and genomic repositories - and contribute with the knowledge and methodology produced to the healthcare system. 2021-2024 Large-scale genomics and health dataSpanish Ministry of Science and Innovation; Instituto de Salud Carlos III ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE LaMarato | It is a project aimed at creating and developing a catalan interhospitalary network to interrogate genetic variants from thousands of genetic tests carried out in patients with rare diseases from the main catalan hospitals. 2021-2024 Genomic and health data Fundacio La Marato de TV3 (catalan foundation) DISCOVERY HealthyCloud | This consortium will contribute a Strategic Agenda towards the European Health Research and Innovation Cloud. The project will work in collaboration with a broad range of stakeholders to ensure that all voices are included and that the results are technically and ethically sound. 2021-2023 Not Applicable European Commission - H2020 Programme DOCUMENTATION B1MG | Beyond 1 Million Genomes aims to create a network of genetic and clinical data across Europe. The project provides coordination and support to the 1+ Million Genomes Initiative (1+MG). This initiative is a commitment of 24 EU countries, the UK and Norway to give cross-border access to one million sequenced genomes by 2022. 2020-2023 Not applicable European Commission - Horizon Europe DATA MANAGEMENT INFRASTRUCTURE METADATA STANDARDS ELIXIR-CONVERGE | An alliance with the goal of Connecting and aligning ELIXIR Nodes to deliver sustainable FAIR life-science data management services. 2020-2023 Data Management and Infectious Diseases European Commission - H2020 Programme DATA MANAGEMENT INFRASTRUCTURE METADATA STANDARDS IHCC | The International HundredK+ Cohorts Consortium aims to create a global platform for translational research ? informing the biological and genetic basis for disease and improving clinical care and population health. 2020-2022 Translational research NIH; The Wellcome Trust; CZI INFRASTRUCTURE METADATA STANDARDS PPCG | The Pan Prostate Cancer Group aims to harmonise and interrogate Whole Genome DNA Sequence data generated around the world from over 2000 men with prostate cancer, with associated transcriptome and methylome data to include men from different clinical categories, and ethnicities. This project is about providing breakthrough advances through analysis of a very large series of Whole Genome DNA data from prostate cancer contributed by many of the leading scientists and clinicians working in prostate cancer genomics. 2019-2024 Cancer Cancer Research UK DATA MANAGEMENT CINECA | Consortium providing a Federated solution enabling population-scale genomic and biomolecular data accessible across international borders accelerating research and improving the health of individuals resident across continents. 2019-2023 Large-scale Genomics and Health Data European Commission - H2020 Programme ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE EASI-Genomics | A project designed to provide easy access to cutting-edge DNA sequencing technologies to researchers from academia and industry, within a framework that ensures compliance with ethical and legal requirements, as well as FAIR and secure data management. 2019-2023 Next Generation Sequencing European Commission - H2020 Programme ACCESS EJP-RD | An European consortium built to create a comprehensive, sustainable ecosystem allowing a virtuous circle between research, care, and medical innovation. 2019-2023 Rare diseases European Commission - H2020 Programme ACCESS DATA MANAGEMENT DOCUMENTATION METADATA STANDARDS EOSC-Life | EOSC-Life brings together the 13 Life Science research infrastructures (LS RIs) to create an open, digital and collaborative space for biological and medical research. The project will publish 'FAIR' data and a catalogue of services provided by participating RIs for the management, storage and reuse of data in the European Open Science Cloud (EOSC). 2019-2023 Not applicable European Commission - H2020 Programme DOCUMENTATION EUCANCan | A federated network aiming at implementing a cultural, technological and legal integrated framework across Europe and Canada, to enable and facilitate the efficient sharing of cancer genomic data. 2019-2023 Cancer European Commission - H2020 Programme DATA MANAGEMENT METADATA STANDARDS The Federated EGA framework: supporting sensitive data management across the ELIXIR Nodes | This project is a direct continuation of the FHD IS with the goal to position the FEGA framework as the core infrastructure driver to support human data sharing for research. 2019-2023 Human genomic data ELIXIR INFRASTRUCTURE UK Biobank | UK Biobank is a large-scale biomedical database and research resource, containing in-depth genetic and health information from half a million UK participants. This project is to archive whole genome sequencing and other genetic data for UK Biobank participants. 2019-2023 Large-scale Genomics and Health Data The Wellcome Trust; UKRI; Amgen; AstraZeneca; GSK; Johnson & Johnson DATA MANAGEMENT INFRASTRUCTURE VEIS | The core mission of VEIS is to create an open ecosystem of technologies that will address and adapt to the requirements of the systems used to analyse and interpret -omics and clinical data in research and application environments in biomedicine. The aim of the project is to leverage the value of the EGA for both industry and society. 2019-2022 Oncology and Rare diseases Generalitat de Catalunya and European Regional Development Fund (ERDF) ACCESS DISCOVERY ELIXIR BEACON IS | This study follows on from a number of earlier activities that have established the ELIXIR Beacon Project. The main aim is to extend the Beacon protocol, developed at EGA, to become the reference ELIXIR Data Discovery product 2019-2021 Not applicable ELIXIR DISCOVERY ELIXIR FHD IS | This project coordinates the delivery of FAIR compliant metadata standards, interfaces, and reference implementation to support the federated ELIXIR network of human data resources. 2019-2021 Human genomic data ELIXIR INFRASTRUCTURE ELIXIR Rare Disease | The Rare Disease Community extends and generalises the system of access authorisation and high volume secure data transfer developed within the EGA. The goal of the Community is to create a federated infrastructure that will enable researchers to discover, access and analyse different rare disease repositories across Europe. It is doing this in partnership with other European infrastructure projects, namely RD-CONNECT, BBMRI-ERIC and E-Rare.2019-2021 Rare diseases ELIXIR INFRASTRUCTURE Solve-RD | Solve-RD - solving the unsolved rare diseases - is a research project funded by the European Commission. It echoes the ambitious goals set out by the International Rare Diseases Research Consortium (IRDiRC) to deliver diagnostic tests for most rare diseases by 2020. The current diagnostic and subsequent therapeutic management of rare diseases is still highly unsatisfactory for a large proportion of rare disease patients - the unsolved RD cases. For these unsolved rare diseases, we are unable to explain the etiology responsible for the disease phenotype, predict the individual disease risk and/or rate of disease progression, and/or quantitate the risk of relatives to develop the same disorder. 2018-2024 Rare diseases European Commission - H2020 Programme ACCESS DATA MANAGEMENT METADATA STANDARDS EuCanShare | An EU-Canada joint infrastructure for next-generation multi-Study Heart research. 2018-2022 Cardiovascular Diseases European Commission - H2020 Programme ACCESS METADATA STANDARDS

  Documentation about/projects-and-funders/projects

• GA4GH

  Standards The EGA is a long-standing supporter of the Global Alliance for Genomics & Health (GA4GH) to enhance responsible sharing of human genetic data through the development of interoperable global standards for human data access. The EGA is one of the founding GA4GH Driver Projects and has contributed to the development and implementation of several GA4GH standards and APIs. Below is a list of the GA4GH standards and APIs that are currently available or planned for implementation at EGA. TechnicalStandards Purpose SpecificationVersion SupportedVersion Implementation Large Scale Genomics htsget A protocol for secure, efficient, and reliable access to sequencing read and variation data. V1.3.0 V1.0.0 Specification Documentation Endpoint Read File Formats (SAM/BAM/CRAM) Specifications for storing next-generation sequencing read data. V3.0.0 V3.0.0 Implementation Example of Usage Variation File Formats (VCF/BCF) The specifications for Variant Call Format Files (VCF) and its binary counterpart BCF. V4.0.0 V2.0.0 V4.0.0 V2.0.0 Implementation Example of Usage Crypt4GH v1.0 Enables direct byte-level compatible random access to encrypted genetic data stored in community standards (e.g. CRAM, VCF) V1.0 V1.0 Specification Documentation Endpoint refget API Enables access to reference sequences using an identifier derived from the sequence itself. V1.2.6 NA Specification RNAget API v1 Provides a means of retrieving data from several types of RNA experiments including (i) feature-level expression data from RNA-seq type measurements and (ii) coordinate-based signal/intensity data similar to a bigwig representation via a client/server model. V1.0.0 NA Documentation Discovery Beacon v2 Supports discovery of genomic variants, phenotypes, and individuals V1.0.1 V0.3 Web UI API Source Code Service Info API v1 The Service Info API is an endpoint for describing GA4GH service metadata, designed for extension and inclusion in other APIs. Service info is used to describe a single service, while Service Registry is used to describe multiple services. V1.0.0 NA Documentation Service Registry API v1 provides information about other GA4GH services, primarily for the purpose of organizing services into networks or groups and service discovery across organizational boundaries. V1.0.0 NA Documentation Data Use Researcher Identities Data Use Ontology (DUO) Allow users to semantically tag genomic datasets with usage restrictions, allowing them to become automatically discoverable based on a health, clinical, or biomedical researcher’s authorisation level or intended use. 2021-02-23 2021-02-23 Specification Documentation Endpoint Authentication & Authorization Infrastructure (AAI) The GA4GH AAI specification leverages OpenID Connect (OIDC) Servers for use in authenticating the identity of researchers desiring to access clinical and genomic resources from data holders adhering to GA4GH standards, and to enable data holders to obtain security-related attributes of those researchers. V1.2.0 V1.2.0 API URI: ega.ebi.ac.uk:8443 Documentation Repository Researcher IDs (passport, visa) Specify the collection of researchers that may access a dataset at any given time, and the credentials they must supply. V1.0.1 V1.0.1 Specification Documentation Endpoint Cloud Tool Registry Service API TRS is a standard API for exchanging tools and workflows to analyze, read, and manipulate genomic data. V2.0.1 NA Documentation Repostiory Data Repository Service API ​DRS API is a standard for building data repositories and adapting access tools to work with those repositories, works with other approved APIs from the GA4GH Cloud Work Stream to allow researchers to discover algorithms across different cloud environments and send them to datasets they wish to analyse. V1.0.3 NA Documentation Repostiory Workflow Execution Service API This API lets users run a single workflow (defined using CWL or WDL) on multiple different platforms, clouds, and environments, and be confident that it will work the same way. The API provides methods to request that a workflow be run, pass parameters to that workflow, get information about running workflows, and cancel a running workflow. V1.0.1 NA Documentation Repostiory Genomic Knowledge Standards Variation Representation v1 Provides a flexible framework of computational models, schemas, and algorithms to precisely and consistently exchange genetic variation data across communities. V1.3.0 EGA team is contributing to including it in in Beacon v2 Specification and Elixir Reference Implementation Documentation Repostiory Clin/ Pheno Data Capture Phenopackets Provides information models with different levels of complexity to enable high level clinical phenotype information as well as deep clinical phenotype information to be exchanged. V2.0.0 Included in Ongoing Submissions EGA team is contributing to including it in in Beacon v2 Specification and Elixir Reference Implementation Documentation Repostiory Driver Project The EGA, jointly coordinated by the EBI and the CRG, was announced, in 2017, to be one of the 15 Driver Projects for GA4GH. Driver Projects are international genomic data initiatives, focussed on real projects and challenges that will guide the development efforts in order to accelerate and enable completely responsible and standarised data sharing by 2022. All chosen Driver Projects make a cross-sectional effort by playing an important role across the different workstreams. Thomas Keane, Jordi Rambla, Mallory Freeberg, and Aina Jené have been named Driver Project Champions for the EGA. All Driver Project Champions will be leading this ambitious initiative for the following years.

  Documentation about/projects-and-funders/ga4gh

• Federated EGA

  Federated EGA Federated EGA Index Overview Map of FEGA status across the world Current status of the FEGA Network Documentation Overview Federated EGA is a global network of repositories enabling secure discovery and access to sensitive human data. Our vision is to accelerate scientific discovery and healthcare breakthroughs by creating the go-to worldwide sensitive human data resource. Our values are: Privacy & Trust: Ensuring privacy of data subjects, security of services and acting with integrity to build community trust.FAIRness: Driving reuse of data through standardisation of metadata and clear access policies.Diversity: Expanding our network and representing global diversity in the data we host to bring benefits worldwide. Federated EGA - European by name, global by nature Federated EGA collaborates with European and global initiatives (GA4GH, ELIXIR, 1+ Million Genomes Framework, GDI), demonstrating that a network for transnational discovery of and access to human data is possible. By providing a solution to emerging challenges around secure and efficient management of human omics and associated data, the FEGA Network fosters data reuse, enables reproducibility, and accelerates biomedical research. For general enquiries or to request more information about Federated EGA, please send an email to fega-info [at] lists [dot] ega-archive [dot] org. Read more about the Federated EGA in our commentary in Nature Genetics! Learn more about joining the Federated EGA Network in our onboarding documentation. Map of FEGA status across the world Current status of the FEGA Network Node Description Joined CEGA Central EGA is managed by the Centre for Genomic Regulation (CRG) and EMBL-EBI. The EGA has been a trusted repository for sensitive data since 2008. CEGA coordinates the FEGA network, hosts central services and the EGA catalogue. 2022 Finland FEGA Finland is hosted by CSC - IT Center for Science Ltd., which is the national ELIXIR Node in Finland. CSC is a state-owned company specialising in providing high-quality IT infrastructure and services for Finnish higher education and research. 2022 Germany The German Human Genome-Phenome archive (GHGA) is part of the German National Research Data Infrastructure (NFDI). It is coordinated by the German Cancer Research Center (DKFZ) and includes over 20 academic partners. 2022 Norway FEGA Norway is a service by ELIXIR Norway, the Norwegian node of the European organisation ELIXIR. University of Oslo as a partner institution in ELIXIR Norway is hosting the service relying on the TSD infrastructure for sensitive data. ELIXIR Norway is a consortium of 5 Norwegian universities and is coordinated by University of Bergen. 2022 Spain FEGA Spain is co-hosted by the Barcelona Supercomputer Center (BSC) and the Centre for Genomic Regulation (CRG), both part of ELIXIR Spain and the Spanish National Infrastructure for Personalised Medicine associated with Science and Technology (IMPaCT). 2022 Sweden FEGA Sweden is hosted by the National Bioinformatics Infrastructure Sweden (NBIS), which legally is part of Uppsala University. NBIS forms the bioinformatics platform at SciLifeLab and constitutes the Swedish node of the European organisation ELIXIR. 2022 Poland FEGA Poland is hosted by Biobank Lodz, which is part of University of Lodz. Biobank Lodz is an element of the infrastructure of the Regional Digital Medicine Centers established by the Medical Research Agency. 2022 Portugal FEGA Portugal is managed by BioData.pt, the distributed infrastructure for Life and Health data for Portugal. This entity is a non-profit association of 15 life sciences R&I organisations spread across the country, and the home of ELIXIR Node in Portugal. 2023 Canada Canadian Genome-phenome Archive is part of the Pan Canadian Genome Library, with the mandate to allow the secure and responsible sharing and analysis of Canadian genomic information. 2024 Switzerland Swiss FEGA is hosted by SIB Swiss Institute of Bioinformatics, which is the national ELIXIR Node in Switzerland, on behalf of the Swiss FEGA Partnership which includes 4 other key partners (ETH Zurich, Health 2030 Genome Center, Swiss Data Science Center and Switch). 2025 Documentation Title Version Description Mission, vision, values Federated EGA Mission, vision, values 1.0 The official Mission-Vision-Values statement for FEGA, produced and formally approved by the FEGA Strategic Committee in September 2025. Structure and Organisation Federated EGA Structure and Organisation 2.0 The structure of the FEGA network and service expectations, responsibilities and commitments. FEGA is organised into three tiers: Central EGA, FEGA Nodes and FEGA Affiliates. Strategic Committee Federated EGA Strategic Committee 1.1 Terms of reference for the FEGA Strategic Committee describe the purpose and objectives of the committee, which is to provide direction and strategic planning for the FEGA network. The committee receives input from, and provides feedback for the EGA Strategic Committee. Operations Committee Federated EGA Operations Committee 1.1 Terms of reference for the FEGA Operations Committee describe the purpose and objectives of the committee, which is to review operational performance and coordinate technical roadmaps of FEGA Nodes and Central EGA. The committee receives advice from, and provides operational reporting to the FEGA Strategic Committee. Guidelines Federated EGA Node Operations Guidelines 2.1 An overview of the operational areas which require resources in order to create a FEGA Node. The document is based on more than 15 years' experience of EMBL-EBI and CRG operating the EGA and initial expericences of the inaugural FEGA Nodes. The operational areas of responsability are in line with the FEGA Maturity Model, which guides establishment and operation of FEGA Nodes. Collaboration Federated EGA Node Collaboration Agreement 1.3 Nodes are welcome to make a copy of this current version of the CA to start its review with their legal teams and understand the responsibilities of joining FEGA. Nevertheless, this version (the one with a watermark) shall not be signed: the official version needs to be obtained from FEGA prior to signing through its official channels. Federated EGA Affiliate Collaboration Agreement 1.0 Affiliates are welcome to make a copy of this current version of the CA to start its review with their legal teams and understand the responsibilities of joining FEGA. Nevertheless, this version (the one with a watermark) shall not be signed: the official version needs to be obtained from FEGA prior to signing through its official channels.

  Documentation about/projects-and-funders/federated-ega

• Implementation of the GDPR

  Data Protection 1 About the EGA The European Genome-phenome Archive (EGA) was formally launched in 2008 at the European Bioinformatics Institute (EMBL-EBI), an outstation of the European Molecular Biology Laboratory (EMBL), to address an identified need for archiving and sharing the results of genome-wide association studies from the Wellcome Trust Case Control Consortium. In late 2012, with the signing of a memorandum of understanding (and subsequent formal agreement in 2016) between EMBL-EBI and the Centre for Genomic Regulation (CRG), the EGA formally became a joint project of the two institutes. The two institutes work together to support the EGA services, including supporting submissions, web site, strategic leadership, and data infrastructure developments. 2 EMBL-EBI & GDPR The EGA is co-managed by EMBL-EBI and CRG. EMBL-EBI is an international organisation established by treaty and has certain privileges and immunities (e.g. exemptions from the application of national law) and also may self-regulate its activities (e.g. establish its own institutional legal framework) within the framework of its founding act of 1973. The General Data Protection Regulation (GDPR) is a European Union (EU) regulation that legislates how organisations can share and process personal data of EU citizens. EMBL places great value in maintaining collaboration with researchers who are subject to GDPR. For that reason, it is of utmost importance for EMBL to handle data received from those collaborators in a secure and responsible manner. Mindful of its public mandate and the sensitivity of the data it handles, EMBL has always ensured a high level of data protection in its activities. Since the introduction of GDPR in May 2018, EMBL has established its internal policy on General Data Protection (IP68), exercising its right to self-regulate its operations,., IP 68 establishes a robust personal data protection framework that provides for data protection principles, enforceable data subject rights and oversight and redress mechanisms offering a level of protection comparable with GDPR. 3 CRG & GDPR The Centre for Genomic Regulation (CRG) is an international biomedical research institute of excellence, created in July 2000 and mainly participated by the Catalan Government. It is a non-profit foundation and its mission is to discover and advance knowledge for the benefit of society, public health and economic prosperity. The CRG is a CERCA center. CERCA is the collective organisation for all research centres of excellence in Catalonia. CERCA ensures these centres develop successfully by promoting synergies and strategic cooperation improving their visibility and the impact of their research and promoting the dialogue amongst both public and private stakeholders. As a legal entity based in Spain and operating within the EU, the CRG ensures the compliance with the GDPR and the legal regulations on personal data protection applicable at the national level, as well as any other legislation that may replace, modify or supplement the above-mentioned in terms of personal data protection. 4 EGA & GDPR EGA GDPR Schema 4.1 Genetic and phenotypic data Within GDPR, there are two main actors: data controllers and data processors. Data controllers are persons or entities which determine the purposes and means that the personal data may be processed, e.g. companies, researchers, or universities. For EGA, the data controller is ultimately the data producer and the submitter(s) who submit the data to EGA. The data controller also creates a Data Access Committee (DAC) who will decide on data access permissions at EGA. Data processors are the persons or entities which process the data on behalf of a data controller. With regard to GDPR, EGA is a data processor as it processes data as instructed by the data controller. GDPR applies to any organisation which accesses personal data from an individual within the EU. Under GDPR, personal data is defined as any data that is identifiable, including names and email addresses as well as health-related and genetic data. EGA does not accept personally identifiable data except genetic and phenotypic data, so all other data submitted to EGA, such as names and addresses, must be pseudonymised. GDPR requires that data controllers implement data protection principles, such as data minimisation, to minimise the risk of data leakage, and protect the rights of the data subjects. As a data processor, EGA has a set of security policies that are followed to minimise the risk of unauthorised data access or data loss. In its role as a data processor, EGA requires all submitters to sign a Data Processing Agreement (DPA) when the submission account is first created. This agreement is only required to be signed once per submitter, and will remain valid for future submissions to EGA. 4.2 Other personal data The EGA also collects personal data as part of our interactions with submitters, data access committees, and researchers accessing data distributed by EGA. The below privacy notices explain what personal data is collected by the specific service you are requesting, for what purposes, how it is processed, and how we keep it secure. Privacy Notices for EGA Title Version Last Updated EGA Data Access Committee Account Privacy Notice for EGA Data Access Committee Account 1.0 February 6, 2019 EGA User Account Privacy Notice for EGA User Account 2.0 February 24, 2026 EGA Helpdesk Service Privacy Notice for EGA Helpdesk Service 2.0 February 24, 2026 EGA Website Service Privacy Notice for EGA Website Service 2.0 February 24, 2026 Documentation Title Version Description EGA Security Overview Security Document 1.1 The EGA Security Document provides an overview of EGA’s practices in ensuring the security of data stored at EGA. EGA Data Processing Agreement Data Processing Agreement 1.5 The Data Processing Agreement must be completed and returned as part of the submission process. Please note that this document is non-negotiable. Authorised Submitters Authorised Submitters Formulary 1.0 The Authorised Submitters Form must be completed and returned as part of the submission process. Please list all those that should have access to the submission account in order to submit to the EGA should be detailed here. Dispute Resolution Any controversy or claim arising out of, or relating to, the DPA (including the enforceability or breach thereof, any question regarding its existence, validity or termination) or relating to the EGA Service shall be resolved using the internal dispute resolution mechanisms of EGA including those related to Data Protection. The EGA’s internal dispute resolution mechanism has the following procedure: EGA OPERATIONAL PHASE: Meetings between EGA staff and the Data Controller.LEGAL MANAGEMENT PHASE: Meetings between legal teams of EMBL, CRG and the Data Controller. DIRECTION MANAGEMENT PHASE: Negotiation between the legal representatives of EMBL, the CRG and the Data Controller. If the internal dispute resolution mechanism doesn’t resolve the controversy or claim the next phase is:ARBITRATION PHASE: Resolution by arbitration under the WIPO Expedited Arbitration Rules (“Rules”).

  Documentation about/privacy-notice

• About

  About What's the EGA? The European Genome-phenome Archive (EGA) is a global network for permanent archiving and sharing of personally identifiable genetic, phenotypic, and clinical data generated for the purposes of biomedical research projects or in the context of research-focused healthcare systems. Jointly managed by the European Bioinformatics Institute (EMBL-EBI) in Cambridge (UK) and the Centre for Genomic Regulation (CRG) in Barcelona, we aim to advance biomedical research and promote personalised medicine worldwide by enabling discovery of and access to human genomic and health research data. The EGA contains data collected from individuals whose consent agreements authorise data release for specific research use to bona fide researchers. We ensure strict security measures to control access to the data and maintain patient confidentiality. With expertise in data management and technical infrastructure, we promote FAIR data reuse and enable researchers to share their data securely. By leveraging public funding and our strategic partnerships, the EGA provides a free service for permanent data storage, data discovery, and secure data access. In addition, we foster a federated network to provide transnational access to human research data in compliance with legal frameworks. For additional information about the EGA, please contact: Helen Parkinson and Mallory Freeberg EMBL European Bioinformatics Institute Arcadi Navarro, Roderic Guigó, and Jordi Rambla Center for Genomic Regulation History The European Genome-phenome Archive was launched in 2008 at the European Bioinformatics Institute (EMBL-EBI), an outstation of the European Molecular Biology Laboratory (EMBL), to address an identified need for archiving and sharing the results of genome-wide association studies from the Wellcome Trust Case Control Consortium. With the signing of a memorandum of understanding in 2013 and a formal agreement in 2016, the EGA became a joint project of EMBL-EBI and the Centre for Genomic Regulation (CRG). The two institutes work together to support the EGA services, including supporting submissions, website, strategic leadership, and data infrastructure developments. In 2022, the Federated EGA was officially launched with the signature of the first five countries: Finland, Germany, Norway, Spain, and Sweden. With more than 20 additional nodes worldwide preparing to join, the Federated EGA aims to become the largest human omics data sharing initiative towards understanding human health and disease. EGA overview If you're a researcher you may need to deposit, manage, or access genomic data in a secure and regulated way. The European Genome-phenome Archive (EGA) is a platform that facilitates these processes, ensuring that sensitive data is stored and shared in accordance with legal and ethical regulations. Submission process To start a submission, you need to become an EGA submitter. For that, you’ll need to sign a Data Processing Agreement (DPA) with us, that defines the terms and conditions under which your data will be processed and shared within the EGA system. The access to each study is controlled by its Data Access Committee (DAC). The DAC is responsible for managing data access requests and ensuring that the release of data is in accordance with the General Data Protection Regulation (GDPR). Please, note that once your data is released, all public metadata related to your study and dataset(s) will be searchable on the EGA website. However, the files are only accessible under controlled access, which means that a DAC has to agree to a previous data access request. Request process It is possible to submit an access request to data stored at the EGA. The DAC assigned to the study will assess the request and, if approved, grant access to the data. Requesters must provide sufficient justification for your request and comply with the intended data usage in order to get access to it. Each dataset is covered by a Data Access Agreement (DAA) that defines the terms and conditions of use for the specified dataset/s. The DAA is created and provided by the DAC, and must be signed by the individual requesting access to the given dataset/s. Download process Once the request for access is approved, the data and metadata can be downloaded. The EGA offers various download options to fit the needs: it is possible to preview files without downloading them, download specific files of interest, or even download terabytes of data. Overall, the EGA provides a secure and regulated environment for depositing, managing, and accessing human data. Regardless of the role - submitter, DAC member, or requester - the EGA provides assistance for each while ensuring that sensitive data is managed in an ethical and responsible manner. More information on how EGA handles data is available in the EGA dataflow.

  Documentation about/ega

• Privacy Notice for Data Access Committee Account

  Privacy Notice for EGA Data Access Committee Account This Privacy Notice explains what personal data is collected by the specific service you are requesting, for what purposes, how it is processed, and how we keep it secure. Note that this service collects personal data directly provided by the user, and also collects personal data from users that is provided by other organisations. 1. Who controls your personal data and how to contact us? European Genome- Phenome Archive - EGA offers a service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects, jointly managed by European Molecular Biology Laboratory – European Bioinformatics Institute (EMBL-EBI) and Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG). EMBL-EBI and CRG represent joint Data Controllers’ of processing of your personal data. They and their Data protection officers may be contacted for data protection queries and for exercising your rights under Section 8. You may contact EMBL-EBI, represented by Mallory Freeberg, by: email at mfreeberg@ebi.ac.uk , orpost at EMBL-EBI, Wellcome Genome Campus, CB10 1SD Hinxton, Cambridgeshire, UK. EMBL’s Data Protection Officer may be contacted by: email at dpo@embl.org, orpost at EMBL Heidelberg, Data protection officer, Meyerhofstraße 1, 69117 Heidelberg, Germany. You may contact CRG, whose EGA team is represented by dr. Jordi Rambla de Argila, by: email at jordi.rambla@crg.eu, orpost at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), Dr.Aiguader 88, PRBB Building, 08003 Barcelona, Spain. CRG Data protection officer may be contacted by: email at dpo@crg.eupost at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), C/ Dr. Aiguader, 88, PRBB Building, 08003 Barcelona, Spain. 2. Which is the lawful basis for processing personal data? We process your personal data on the grounds of important public interest. For monitoring your activities on the website, we process your personal data on the grounds of important public interest. Such legal basis is found in Article 5(1)(a) of EMBL Internal Policy No 68 on General Data Protection (hereinafter IP 68), which is equivalent to Article 6 (1)(e) of the EU General Data Protection Regulation (hereinafter GDPR) and upon which personal data are processed for the achievement of the aims laid down in 1973 agreement establishing EMBL, such as the promotion of the cooperation in the fundamental research, in the development of advanced instrumentation and in advanced teaching in molecular biology and dissemination of information. 3. What personal data is collected from users of the service? How do we use this personal data? We collect the following personal data from you: NameEmail addressTitle/PositionOrganisationOrganisational affiliationBusiness addressTelephone numberIP addressesDate and time of a visit to the service websiteOperating systemAmount of data transmittedBrowserUsernamePassword The data controller will use your personal data for the following purposes: To provide DAC user account and authenticated access to the service,To publicly publish some information to facilitate scientific research,To better understand the needs of the data subjects and guide future improvements of the service,To create anonymous usage statistics (from number of DACs, datasets per DAC). 4. Who will have access to your personal data? The personal data will be disclosed to: Authorised staff in the data controller’s institutions acting on data controller`s behalf and instructions (for all user account data),The general public via Internet will get access to your name, email address, business address, telephone number and organisation you belong to. 5. Will your personal data be transferred to third countries (i.e. countries not part of EU/EEA) and/or international organisations? Data categories ‘name`, `email address`, `telephone number`, `business address`; `organisation’ of the DAC user are published on the Internet. They thus become accessible to recipients in countries outside the European Economic Area. Insofar as the second joint controller may be subject to GDPR, data transfer to and from the first joint controller (EMBL-EBI), is necessary for important reasons of public interest embedded in the aims of EMBL and justified in the Article 9(4) of IP 68 (equivalent to Article 49(1)(d) of GDPR) read in conjunction with EMBL`s 1973 establishing agreement and Article 179(2) of the Treaty on the Functioning of the European Union 6. How long do we keep your personal data? Any personal data directly obtained from you will be retained as long as the service is live. Such duration serves the purpose of enabling scientific research and ensures legal compliance and facilitates internal and external audits if they arise. By contrast, the log files for the data categories related to anonymous usage statistics (raw web service logs) are processed only for 30 days and thereafter erased. 7. The joint Data Controllers provide these rights regarding your personal data You have the right to: Not be subject to decisions based solely on an automated processing of data (i.e. without human intervention) without you having your views taken into consideration.Request at reasonable intervals and without excessive delay or expense, information about the personal data processed about you. Under your request we will inform you in writing about, for example, the origin of the personal data or the preservation period.Request information to understand data processing activities when the results of these activities are applied to you. It must be clarified that rights under points 4 and 5 are only available whenever you need support whilst using our website. For other processing based on the grounds of important public interest you cannot exercise your rights to object, rectify or erase your personal data according to the Article 13(2)(a)(b) of IP 68 (equivalent to Article 17(3)(b)(d) and Article 21(6) of the GDPR). 8. Supervisory authority If you wish to complain against the processing of your personal data, you may do so by post at: EMBL Heidelberg, Data Protection Committee, Meyerhofstraße 1, 69117 Heidelberg, Germany, or Autoritat Catalana de Protecció de Dades (Catalan Data Protection Authority), C/Rosselló 214, Esc A, 1r 1a, Barcelona 08008, Spain. Published at: February 6, 2019

  Documentation data-protection/privacy-notice/ega-dac

• German early-onset prostate cancer cohort of the Pan-Prostate Cancer Genome (PPCG) project

  Prostate cancer is the most frequent malignant tumor in males and the second most frequent cause of cancer-related death. Currently, in Germany, more than 60,000 prostate cancers are diagnosed every year. Although most of these patients are treated in a curative attempt, more than 10,000 German men die from prostate cancer annually. Owing to the demographic changes of our society, a further doubling of prostate cancer incidences during the next 20 years is expected. Prostate cancer is generally considered a tumor of elderly men. However, a fraction of prostate cancers are diagnosed at the age of 55 years or less. For several reasons, these “early onset prostate cancers” may represent a key entity for the understanding of prostate cancer biology. First, it is likely that early onset prostate cancers represent a distinct molecular subgroup of prostate cancer (PCa), potentially characterized by relatively small numbers of genetic changes, some of which may be particularly strong driver mutations for PCa development. Second, a fraction of prostate cancers in young individuals could represent classical prostate cancers that are detected at a very early stage and might therefore have accumulated molecular changes/mutations occurring that are most instrumental for prostate cancer early detection. Third, PCa with hereditary backgrounds are likely to accumulate in the age group below 55 years. A comparison with other sample sets (e.g. from other ICGC consortia), a systematic genomic analysis of young men with PCa could therefore lead to the detection of mechanisms for hereditary PCa. Fourth, a better understanding of these tumors is particularly relevant as finding optimal treatment regimens is most critical in young cancer patients. We are analyzing the entire genomic DNA sequences of at least 200 PCas (and matched non-tumorous DNA) of young men (≤ 55y), to at least 30 fold coverage, and integrate single-nucleotide variants and genomic structural variations with differential methylation, mRNA and miRNA expression data.Tissues were collected at the University Medical Center Hamburg-Eppendorf. Sequencing was performed at DKFZ and NCT (Heidelberg), EMBL (Heidelberg), and MPIMG (Berlin). Data management and bioinformatic data analyses is being conducted at DKFZ.

  Study EGAS00001003373

• Cell-free DNA TAPS for early cancer detection

  Multimodal, genome-wide characterization of epigenetic and genetic information in circulating cell-free DNA (cfDNA) could enable more sensitive early cancer detection. However, due to technological challenges associated with DNA methylation sequencing in low input cfDNA samples, most studies have been limited by DNA damage caused by bisulfite sequencing, or the qualitative nature of enrichment-based sequencing. Recently, we developed TET-assisted Pyridine Borane Sequencing (TAPS), which is a mild, bisulfite-free method for base-resolution direct DNA methylation sequencing. Here we optimized TAPS for cfDNA (cfTAPS) to provide high-quality and high-depth whole-genome cell-free methylomes. We applied cfTAPS to 85 cfDNA samples from patients with hepatocellular carcinoma (HCC) or pancreatic ductal adenocarcinoma (PDAC) and non-cancer controls. From just 10 ng cfDNA (1-3 mL of plasma), we generated the most comprehensive cfDNA methylome to date. We demonstrated that cfTAPS provides multimodal information about cfDNA characteristics, including DNA methylation, tissue of origin, and DNA fragmentation. Integrated analysis of these epigenetic and genetic features enables accurate identification of early HCC and PDAC.

  Study EGAS00001004962

• PanCuRx Translational Research Initiative

  The goal of the PanCuRx TRI is to seek solutions to the high fatality rate of pancreatic adenocarcinoma (PDAC), the most common type of pancreatic cancer, by generating new knowledge about the genetics and biology of the disease, mechanisms of how tumours grow and tailored treatment options. PDAC is the fourth leading cause of cancer death in Canada and is expected to become the second-leading cause of cancer death within the next decade. The current five-year survival rate of eight per cent is the lowest of all epithelial cancers. There are major clinical challenges to treating the disease, including the fact that PDAC spreads to other parts of the body early so surgical removal of the tumour benefits few patients, that PDAC has proven relatively resistant to systemic therapies such as chemotherapy and that there has been limited benefit from the use of newer molecular targeted agents. The PanCuRx team has created the world’s first resource of tumour-purified PDAC whole genomes; more than 500 PDAC samples, with combined clinical annotation, have been successfully sequenced and analyzed at the Ontario Institute for Cancer research in Toronto. The resulting clinical genomic resource created from this data has led to multiple new findings that have established a framework to better understand PDAC biology and lays the foundation for new genomic approaches to better understanding the disease. The team also launched a clinical trial called COMPASS (Comprehensive Molecular Characterization of Advanced Ductal Pancreas Adenocarcinoma for Better Treatment Selection: A Prospective Study), which is recruiting patients with advanced PDAC (both locally advanced and metastatic) at The Princess Margaret Cancer Centre (PM) in Toronto. The study uses the molecular results from individual patient tumours to guide selection of better second line treatment on a case-by-case basis. The primary objective of the initial study was to assess the feasibility of collecting tumour materials from patients with advanced PDAC and delivering results within 56 days of biopsy. Having achieved this objective, the trial has expanded to other cancer centres across Canada. Pancreatic cancer is one of the most deadly forms of cancer and outcomes have not improved in four decades. The PanCuRx initiative is providing a better understanding of the disease and actively applying new knowledge to cancer patients through clinical trials. This knowledge will help to improve quality of life and prolong survival for pancreatic cancer patients worldwide.

  Study EGAS00001002543

• Canadian prostate cancer samples (CPC-GENE) for PanProstate study

  CPC-GENE has sequenced the genomes of 350 intermediate risk prostate cancers to identify genetic signatures that differ in cancers that responded well to treatment compared with those that did not. CPC-GENE also has sequenced multiple regions of prostate cancer from the same gland to determine if and how the genetic make-up of prostate cancer varies within an individual man’s prostate

  Study EGAS00001003037

• Reconstructing the dispersals and adaptive history of Bantu-speaking populations in Africa and North America

  Bantu languages are spoken by ~310 million Africans, yet the genetic history of Bantu-speaking populations remains largely unexplored. We generated genomic data for 1,318 individuals from 35 populations in western central Africa, where Bantu languages originated. We found that early Bantu speakers first moved southward, through the equatorial rainforest, before spreading toward eastern and southern Africa. We also found that genetic adaptation of Bantu speakers was facilitated by admixture with autochthonous populations, particularly for the HLA and LCT loci. Finally, we identified a major contribution of western central African Bantu speakers to the ancestry of African Americans, whose genomes present no strong signals of natural selection. Together, these results highlight the contribution of Bantu-speaking peoples to the complex genetic history of Africans and African Americans.

  Study EGAS00001002078

• Single cell multi-omic data of glioblastoma evolution under therapy

  We report a single-cell multi-omics atlas of GBM longitudinal specimens that represents decades of biobanking. We identify novel cell-intrinsic and cell-extrinsic targets for therapy development which we validate in situ and in low-passage patient-derived cell lines. We identify novel genetic correlates of the mesenchymal cellular phenotype. These studies integrate disparate findings in the literature around hypermutation status and immunogenicity as well as the source of the mesenchymal shift at recurrence.

  Study EGAS00001004909