3798 results for "*oma"

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• Raw data for "Spatial and temporal transcriptomics of medulloblastoma with chromothripsis identifies multiple genetic clones that resist to treatment and lead to relapse"

  FASTQ files from Illumina sequencing of 10x Visium experiments.

  Dataset EGAD00001010260

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__Oesophageal_adenocarcinoma

  The 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 (40X and 20X depth respectively). 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 EGAS00001003702

• Transcriptomic analysis of liver CD8+ T cells

  Sorted single CD8+T cells expressing CD14 from human liver for SMARTSeq2. Livers processed: Kucykowicz et al STAR Prot 2022:pubmed.ncbi.nlm.nih.gov/35516846/ Published: Pallett et al Nature 2022 Tissue CD14+CD8+T-cells are reprogrammed by myeloid cells and modulated by LPS The liver is bathed in bacterial products including LPS transported from the intestinal portal vasculature, but maintains a state of tolerance exploited by persistent pathogens and tumours1,2,3,4. The cellular basis mediating this tolerance, yet allowing a switch to immunity or immunopathology, needs to be better understood for successful immunotherapy of liver diseases. Here we show that a variable proportion of CD8+T-cells compartmentalised in the human liver co-stain for CD14 and other prototypic myeloid membrane proteins; CD14+CD8+T-cells preferentially accumulate within the donor pool in liver allografts, amongst hepatic virus-specific and tumour-infiltrating responses, and in cirrhotic ascites. CD14+CD8+T-cells exhibit increased turnover, activation and constitutive immunomodulatory features with high homeostatic IL-10/IL-2 production directly ex vivo, and an enhanced capacity to rapidly produce antiviral/anti-tumour cytokines upon TCR engagement. This CD14+CD8+T-cell profile can be recapitulated by acquisition of membrane proteins, including the LPS receptor complex, from mononuclear phagocytes, resulting in augmented tumour killing by TCR-redirected T-cells in vitro. CD14+CD8+T-cells express integrins and chemokine receptors favouring interactions with the local stroma, which can promote their induction through CXCL12. LPS can also increase the frequency of CD14+CD8+T-cells in vitro and in vivo, and skew their function towards the production of chemotactic and regenerative cytokines. Thus, bacterial products in the gut-liver axis and tissue stromal factors can tune liver immunity by driving myeloid instruction of CD8+T-cells with immunomodulatory capacity. For the analysis of the single cell transcriptome two intrahepatic perfusate samples were isolated and frozen at -80 'C for storage prior to transportation to Newcastle, UK. Once thawed in pre-warmed HBSS containing 0.001% DNaseI, intrahepatic leukocytes were sorted by FACS to index classical mononuclear phagocytes (MNP) defined as Singlets, CD3-CD56-CD19-CD14hiHLA-DR+ or CD14± CD8+T-cells as follows: Singlets, CD3+CD56-CD19-CD4-CD8+V7.2- and split in to CD14± based on an isotype control. Single cells were sorted into 96-well skirted LoBind plates (Eppendorf) containing 5 µL lysis buffer (TCL buffer [Qiagen], supplemented with 1% b-mercaptoethanol [Sigma Aldrich; Merck]) on a BD Bioscience FACSFusion. The sorted plates were subsequently immediately sealed, centrifuged, and placed on dry ice to flash-freeze the cell lysate and stored at -80 'C. A modified SMART-seq2 protocol57 was performed on the single flow cytometry sorted-cells as previously described58. After cDNA generation, libraries were prepared (384 cells per library) using the Illumina Nextera XT kit (Illumina). Each library was sequenced to achieve a minimum depth of 1-2 million raw reads per cell using an Illumina HiSeq 4000 using v. 4 SBS chemistry to generate 75-bp paired-end reads.

  Study EGAS00001006885

• Familial Melanoma Sequencing

  In this experiment we have sequenced the exome of 15 individuals from eight families who have familial melanoma. By sequencing the exome we hope to be able to identify new genes that are associated with this disease.

  Study EGAS00001000017

• NOTCH1 fusion genes in pediatric T-cell lymphoblastic lymphoma hallmark a common high-risk subgroup with blood TARC levels as possible biomarker

  T-cell lymphoblastic lymphoma (T-LBL) is a common pediatric malignancy accounting for approximately 20% of the non-Hodgkin lymphomas during childhood. Survival rates of T-LBL are ~80%, but outcome after relapse is dismal, with salvage rates reaching only ~15. Considering the extremely poor prognosis after relapse and absence of clinically relevant high-risk genetics, there is an urgent need for the identification of molecular risk factors and new prognostic biomarkers in T-LBL, as well as identification of new therapeutic strategies. In this study we present a novel entity of high-risk pediatric T-LBL patients characterized by previously unknown NOTCH1 gene fusions and highly elevated blood TARC levels

  Study EGAS00001007703

• OpACIN-neo – A Multicenter Phase 2 Study to identify the Optimal neo-Adjuvant Combination scheme of Ipilimumab and Nivolumab – RNA sequencing

  The outcome of patients with macroscopic stage III melanoma is poor. Neoadjuvant treatment with ipilimumab plus nivolumab at the standard dosing schedule induced pathological responses in a high proportion of patients in two small independent early-phase trials. However, toxicity of the standard ipilimumab plus nivolumab dosing schedule was high, preventing its broader clinical use. The aim of the OpACIN-neo study (NCT02977052) to identify a dosing schedule of ipilimumab plus nivolumab that is less toxic but equally effective. 86 patients with macroscopic stage III melanoma were randomised to one of three dosing schedules: arm A, two cycles of ipilimumab 3 mg/kg plus nivolumab 1 mg/kg once every 3 weeks; arm B, two cycles of ipilimumab 1 mg/kg plus nivolumab 3 mg/kg once every 3 weeks; or arm C, two cycles of ipilimumab 3 mg/kg once every 3 weeks directly followed by two cycles of nivolumab 3mg/kg once every 2 weeks. Within the first 12 weeks, grade 3–4 immune-related adverse events were observed in 12 (40%) of 30 patients in group A, six (20%) of 30 in group B, and 13 (50%) of 26 in group C. Pathological responses occurred in 24 (80%) patients in group A, 23 (77%) in group B, and 17 (65%) in group C. The 2-year estimated relapse-free survival was 84% for all patients, 97% for patients achieving a pathologic response and 36% for nonresponders (p<0.001). High tumor mutational burden (TMB) and high interferon-gamma-related gene expression signature score (IFN-γ score) were associated with pathologic response and low risk of relapse; pathologic response rate (pRR) was 100% in patients with high IFN-γ score/high TMB, patients with high IFN-γ score/low TMB or low IFN-γ score/high TMB had pRRs of 91% and 88%; while patients with low IFN-γ score/low TMB had a pRR of only 39%. These data demonstrate long-term benefit in patients with a pathologic response and show the predictive potential of TMB and IFN-γ score.

  Study EGAS00001004833

• Comprehensive Transcriptional Analysis of Early Stage Urothelial Carcinoma using whole transcriptome sequencing

  The expression profile and sequence variants of 476 early stage urothelial carcinoma were studied using whole transcriptome sequencing. RNA-Seq libraries were prepared by Ribo-Zero treatment of total-RNA followed by library preparation using ScriptSeq (both Epicentre/Illumina). RNA-Seq libraries were paired-end sequenced (2x 101 bp) on Illumina HiSeq 2000 and the resulting fastq files were processed using tools from the Genome Analysis Toolkit (GATK and from the Tuxedo suite. Access to the sequence data (mapped and un-mapped bam and vcf files), containing person identifying information, needs signature on a controlled access form, and can be accessed at The European Genome-phenome Archive (EGA) following request. An expression matrice of FPKM values are available without restriction at ArrayExpress (E-MTAB-4321).

  Study EGAS00001001236

• Genome-wide genetic and epigenetic dataset of pancreatic acinar cell carcinomas

  Pancreatic acinar cell carcinoma (ACC) is an aggressive exocrine tumor with largely unknown biology. To identify potential targets for personalized treatment, integrative genome- and epigenome-wide analyses were performed. The results show frequently aberrant DNA methylation, abundant chromosomal amplifications and deletions, and mutational signatures suggesting defective DNA repair. In contrast to pancreatic ductal adenocarcinoma, no recurrent point mutations are known. The tumor suppressors ID3, ARID1A, APC, and CDKN2A are frequently impaired also on the protein level and thus potentially affect ACC tumorigenesis. Consequently, this work identifies potential novel therapeutic targets in ACC for drugs recently approved for precision cancer therapy.

  Study EGAS00001002533

• Clinical activity and molecular correlates of response to atezolizumab alone or in combination with bevacizumab versus sunitinib in renal cell carcinoma

  We examined pre-treatment tumors from participants of the IMmotion150 trial. Biomarker analyses indicate that high angiogenesis gene expression was associated with improved PFS within the sunitinib arm, and high T-effector/IFNγ response (Teff) gene expression with longer PFS in atezolizumab + bevacizumab vs sunitinib patients. In high Teff tumors, concomitant high myeloid inflammation was associated with worse PFS in the atezolizumab monotherapy arm; adding bevacizumab to atezolizumab in this subgroup improved PFS vs atezolizumab. Molecular profiles suggest that prediction of outcomes with VEGF inhibitors and immunotherapy may be possible in mRCC, and bevacizumab may overcome myeloid inflammation-associated atezolizumab resistance.

  Study EGAS00001002928

• Molecular determinants of response to PD-L1 blockade across tumor types

  Immune checkpoint inhibitors targeting the PD-1/PD-L1 axis lead to durable clinical responses in subsets of cancer patients across multiple indications, including non-small cell lung cancer (NSCLC), urothelial carcinoma (UC) and renal cell carcinoma (RCC). Herein, we complement PD-L1 immunohistochemistry (IHC) and tumor mutation burden (TMB) with RNA-seq in 366 patients to identify unifying and indication-specific molecular profiles that can predict response to checkpoint blockade across these tumor types. Multiple machine learning approaches failed to identify a baseline transcriptional signature highly predictive of response across these indications. Signatures described previously for immune checkpoint inhibitors also failed to validate. At the pathway level, significant heterogeneity was observed between indications, in particular within the PD-L1+ tumors. mUC and NSCLC were molecularly aligned, with cell cycle and DNA damage repair genes associated with response in PD-L1- tumors. At the gene level, the CDK4/6 inhibitor CDKN2A was identified as a significant transcriptional correlate of response, highlighting the association of non-immune pathways to the outcome of checkpoint blockade. This cross-indication analysis revealed molecular heterogeneity between mUC, NSCLC and RCC tumors, suggesting that indication-specific molecular approaches should be prioritized to formulate treatment strategies.

  Study EGAS00001004343

• Molecular subsets in renal cancer determine outcome to checkpoint and angiogenesis blockade

  We conducted integrated multi-omics evaluation of 823 tumors from advanced renal cell carcinoma (RCC) patients and identified molecular subsets associated with differential clinical outcomes to angiogenesis blockade alone or with a checkpoint inhibitor. Unsupervised transcriptomic analysis revealed six molecular subsets with distinct angiogenesis, immune, cell cycle, metabolism, and stromal programs. While sunitinib was effective in subsets with high angiogenesis, atezolizumab+bevacizumab improved clinical benefit in tumors with high T-effector and/or cell cycle transcription. Somatic mutations in PBRM1 and KDM5C associated with high angiogenesis and AMPK/Fatty acid oxidation gene expression, while CDKN2A/B and TP53 alterations were more prevalent in tumors with increased cell cycle and anabolic metabolism. Sarcomatoid tumors exhibited low prevalence of PBRM1 mutations and angiogenesis markers, frequent CDKN2A/B, BAP1 and TP53 alterations, and increased PD-L1 expression. These findings can be applied to molecularly stratify advanced RCC patients, explain improved outcomes of sarcomatoid tumors to checkpoint blockade, and develop personalized therapies.

  Study EGAS00001004353

• RP-1843 Arcagen - Gastrointestinal rare cancers (GI)

  Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here we are submitting two datasets that contain NGS files from gastrointestinal rare cancers (n=119): - Dataset 1 (32 patients): Mesothelioma of the peritoneum (n=21) and Pseudomyxoma peritonei/mucinous adenocarcinoma of the appendix (n=11) - Dataset 2 (87 patients): Intra-hepatic cholangiocarcinoma (n=47), Extra-hepatic, cholangiocarcinoma (n=16), Not specified Cholangiocarcinoma (n=9), Small bowel adenocarcinoma (n=6) and other rare GI cancer (n=9)

  Study EGAS00001006299

• an integrated molecular study of clear cell renal cell carcinoma (ccRCC) including whole-genome/exome and RNA sequencing as well as array-based gene expression/copy-number/methylation analyses

  Study EGAS00001000509

• Integrated genomic analyses reveal molecular correlates of clinical response and resistance to atezolizumab in combination with bevacizumab in advanced hepatocellular carcinoma

  Atezolizumab (anti–programmed death-ligand 1 [anti-PD-L1]) and bevacizumab (anti-vascular endothelial growth factor [anti-VEGF]) combination therapy has become the new standard of care in patients with unresectable hepatocellular carcinoma. However, potential predictive biomarkers and mechanisms of response and resistance remain less understood. We report integrated molecular analyses of tumor samples from 358 patients enrolled in the GO30140 phase 1b or IMbrave150 phase 3 trials who were treated with atezolizumab combined with bevacizumab, atezolizumab alone, or sorafenib. Pre-existing immunity assessed by high expression of CD274 (PD-L1 mRNA), T-effector signature, and intratumoral CD8+ T cell density were associated with response and better clinical outcomes with the combination treatment. Less clinical benefit was associated with high regulatory T cell (Treg) to effector T-cell ratio and high expression of oncofetal genes such as GPC3 and AFP. Improved outcomes from the combination vs atezolizumab alone appeared to be associated with high expression of KDR (VEGFR2), Treg, and myeloid inflammation signatures, indicating anti-VEGF may contribute by targeting these axes. These findings were further validated by transcriptome analysis of paired pre- and post-treatment biopsies, in situ analysis by multiplex IHC and digital pathology, and in vivo study of an immunogenic hepatocellular carcinoma mouse model. Our findings highlight that anti-VEGF therapy might augment antitumor immunity and enhance anti–PD-L1 immunotherapy by targeting VEGF-mediated angiogenesis, Treg proliferation, and myeloid cell inflammation. Furthermore, our study identified candidate biomarkers for predicting response and resistance to anti–PD-L1 and anti-VEGF combination therapy.

  Study EGAS00001005503

• SPECIAL: Dissecting the melanoma ecosystem one cell at the time during immunotherapy

  The aim of this study was to identify potential biomarkers of response to immunotherapy (anti-PD1-based) as well as gain understanding of the biological mechanism of therapy resistance (either intrinsic or acquired) in melanoma patients. Single cell RNA sequencing was performed from pre- and on-treatment (2-3 weeks after immunotherapy) metastatic biopsies from stage III and IV melanoma patients.

  Study EGAS00001006488

• Evolutionary Genome Analysis of Transformation into Small Cell Carcinomas from Lung Adenocarcinomas

  Anecdotal case have been reported lung adenocarcinoma could occasionally transform into small cell carcinoma. Most of the reported cases were EGFR-mutant lung adenocarcinomas that transform into small cell carcinoma during EGFR tyrosine kinase inhibitor treatment. However, some cases also indicate lung adenocarcinomas without EGFR mutation could also transform into small cell carcinomas. Here we investigate this transformation process by whole genome sequencing of transformed small cell carcinomas as well as serially acquired samples of lung adenocarcinoma into small cell carcinomas.

  Study EGAS00001001757

• Comprehensive Genomic Characterization of Refractory Multiple Myeloma Reveals a Complex Mutational and Structural Landscape Associated with Drug Resistance (H067)

  Outcome of patients with multiple myeloma (MM) refractory to immunomodulatory agents (IMiDs) and proteasome inhibitors (PIs) is still very poor. To elucidate the genetic landscape of relapsed/refractory MM (RRMM) we performed whole genome and transcriptome sequencing of 39 heavily pretreated RRMM patients with at least double refractoriness revealing complex structural changes and a high mutational load (H067/K08K). We found a median of 67 structural variants and 116 nonsynonymous exonic mutations per patient. Assessment of oncogenic drivers showed NRAS, BRAF, TP53, KRAS, SLC4A7, FAM46C, DIS3, RB1, KMT2C, MLLT4, EWSR1, HCFC2, and COPS3 as significantly mutated. We found multiple genomic regions with bi-allelic events affecting known tumor suppressor genes, most frequently TP53, RB1, and TRAF3. Supervised analysis of mutational signatures showed a major contribution of Cosmic signature 6 associated with deficiency in DNA mismatch repair and the ‘BRCAness’ signature which coincided with mutations in genes known to confer PARP inhibitor sensitivity. Recurrently mutated gene networks included genes with relevance for PI and IMiD activity, the latter including in particular members of the Cereblon and the COP9 signalosome complex. In conclusion, this comprehensive genomic characterization revealed a complex mutational and structural landscape in RRMM and highlights potential implications for therapeutic strategies.

  Study EGAS00001004363

• Methylation-based classification of human mesenchymal chondrosarcoma

  We applied methylome and copy number profiling to a set of 45 well characterized MCS cases to evaluate their potential diagnostic value. Notably, the findings were reproducible also when analysing the round cell and cartilaginous component separately. Furthermore, four outliers were identified by methylome profiling for which the diagnosis had to be revised. Methylome profiling represents a sensitive, specific and reliable tool to support the diagnosis of MCS, particularly if only the round cell component is obtained in a biopsy and the diagnosis is not suspected. It can furthermore aid in confirming the diagnosis in case RNA sequencing for the HEY1::NCOA2 fusion transcript is not available.

  Study EGAS00001007042

• Whole genome sequencing of primary and metastatic Melanoma cases in an Australian cohort.

  Melanoma is the fourth most common cancer in Australia and the leading cause of cancer death in young adults. The Australian Melanoma Genome Project (AMGP) is analysing whole genomes from melanomas. We include the results of whole genome sequencing (WGS) for a number of datasets that include cutaneous, acral and mucosal melanoma subtypes.

  Study EGAS00001001552

• Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell RCC-- CA209-025

  Immune checkpoint inhibitors targeting the PD-1 pathway have transformed the management of many advanced malignancies, including clear cell renal cell carcinoma (ccRCC), but the drivers and resistors of PD-1 response remain incompletely elucidated. Here, we analyzed 592 tumors collected from advanced ccRCC patients enrolled in prospective clinical trials of treatment with PD-1 blockade (or mTOR inhibition as control arm) by whole-exome and RNA-sequencing, integrated with immunofluorescence analysis, to define the somatic alteration landscape of late-stage ccRCC and to uncover the immunogenomic determinants of therapeutic response. While conventional genomic markers (tumor mutation burden, neoantigen load) and degree of CD8+ T cell infiltration were not associated with clinical response, we discovered numerous chromosomal alterations in advanced ccRCC associated with response or resistance to PD-1 blockade. These advanced tumors were highly CD8+ T cell infiltrated, with only 22% and 5% with an immune desert and immune excluded phenotype, respectively. Our analysis revealed that CD8+ infiltrated tumors are depleted of favorable PBRM1 mutations and are enriched for unfavorable chromosomal losses of 9p21.3 when compared to non-infiltrated tumors. These data demonstrate how the interplay of somatic alterations and immunophenotypes impacts therapeutic efficacy.

  Study EGAS00001004292

• 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

• Methylome of medulloblastoma data (MB_COMICS cohort)

  Study EGAS00001007815

• 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

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