Search Results - EGA European Genome-phenome Archive

McGill EMC Release 4 for assay "ATAC-seq"

McGill EMC Release 4 for assay "ATAC-seq": Sequencing of transposase-accessible chromatin as described by Buenrostro et al. (Nature Methods 10, 1213?1218 (2013) doi:10.1038/nmeth.2688)

Dataset EGAD00001001300

release_2: ICGC PedBrain: whole exome sequencing and Target-Seq

Dataset EGAD00001001624

scRNA-seq of monocultures and co-cultures of PDAC-PDOs and CAFs

scRNA-seq of monocultures and co-cultures of patient-derived PDAC organoids and matched CAFs. 3 sample sets per patient.

Dataset EGAD00001009655

Dataset to study clonal evolution in iAMP21 patient SJBALL021901 using scWGS-seq

scWGS-seq of flow sorted blast and normal cells from SJBALL021901 with 71 high quality cells sequenced (67 blast and 4 normal)

Dataset EGAD00001009755

Impact of BRCA mutation type in non-tumorous breast tissue transcriptome

To investigate the transcriptomic difference between BRCA1 vs. BRCA2 carriers, RNA sequencing was carried out.

Study EGAS00001004890

RNAseq cutaneous and uveal melanoma liver metastases

RNA sequencing analyses of tumor liver metastases from untreated cutaneous melanoma (CM) and uveal melanoma (UM) patients.

Study EGAS00001004794

RNA sequencing of human ILC3 from lymphoid organs and blood

Rna sequencing of purified human group 3 innate lymphoid cells from non-reactive lymph nodes and spleen, inflamed tonsils and peripheral blood.

Dataset EGAD00001003704

RNA Sequencing of paediatric patients with B lymphoblastic leukemia

RNA sequencing was performed on 54 bone marrow samples at diagnosis of paediatric patients with B lymphoblastic leukemia.

Dataset EGAD00001005103

RNA data for EGAS00001004660

RNA data for EGAS00001004660, "Aggressive PDACs show hypomethylation of repetitive elements and the execution of an intrinsic IFN program linked to a ductal cell-of-origin"

Dataset EGAD00001006539

Total RNA sequencing in M1911

The dataset comprises total RNA sequencing data obtained from two samples of testicular tissue from the individual M1911, who was diagnosed with meiotic arrest.

Dataset EGAD00001008639

Plasma RNA sequencing

Plasma RNA sequencing (consists of 70 cases)

Dataset EGAD00001008836

Patient TSO500 RNA

Original patient tumours from which PDX models were derived. TruSight Oncology RNA panel for 2 samples, sequenced over 4 lanes each, gave 8 pairs of fastq files

Dataset EGAD00001009659

Ovarian Carcinosarcoma DNA and RNA sequencing of patient samples in the UK cohort.

Ovarian Carcinosarcoma DNA and RNA sequencing of patient samples in the UK cohort (n=18).

Dataset EGAD00001011068

Single-cell RNA sequencing of RCC patients

Single-cell RNA sequencing was performed on viable frozen tumor dissociated cells from three RCC patients. The raw data is available as fastq files.

Dataset EGAD00001011045

Human serum small non-coding RNA sequencing

Human small non-coding RNA sequencing of serum from sons of PCOS mothers (n=9) and sons of control mothers (n=9), see publication for details.

Dataset EGAD00001010165

RNA sequencing of AD, MCI and control OM cells

Total RNA sequencing of cultured OM cells derived from patients with Alzheimer's disease (AD), individuals with mild cognitive impairment (MCI) and cognitively healthy controls.

Dataset EGAD00001008707

Dataset for RNA PCNSL

RNA sequencing of 19 samples from PCNSL tumors. Sequencing was performed on a HiSeq X Ten using Illumina TruSeq Stranded mRNA Kit. Sequencing was always paired.

Dataset EGAD00001011119

Single-cell RNA and TCR sequencing of 40 advanced HCC biopsies.

Single-cell RNA and TCR sequencing of 40 advanced HCC pre-treatment biopsies from 38 patients.

Dataset EGAD00001011347

Dataset includes cell-free ChIP-seq data of 268 samples (from 61 self-declared healthy donors, four patients with acute myocardial infarction, 29 patients suffering from autoimmune, metabolic, or viral liver diseases and 56 metastatic colorectal carcinoma (CRC) patients). DNA libraries preparation is documented in the methods section. Libraries were paired end sequenced by Illumina NextSeq 500 and aligned to the human genome (hg19) using bowtie2 (2.3.4.3) with ‘no-mixed’ and ‘no-discordant’ flags. This dataset includes fastq and BAM files of all samples.

Dataset EGAD00001006811

scRNA-seq dataset of patient with immune dysregulation

scRNA-seq dataset on a patient (P_IKZF2-het) presenting with immune dysregulation. This dataset contains raw and processed files from scRNA-seq performed on samples using the 10x Genomics Chromium Controller with the Chromium Single Cell 3′ Reagent Kit (v3 chemistry). There are three paired-end (75 bp) fastq files (I1, R1, R2) and three processed files generated with 10x Genomics Cell Ranger v3.0.2 software against GRCh38 human reference transcriptome (scrnaseq_P_IKZF2-het_barcodes.tsv.gz, scrnaseq_P_IKZF2-het_features.tsv.gz, scrnaseq_P_IKZF2-het_matrix.mtx.gz).

Dataset EGAD00001008443

BLUEPRINT September 2016, ChIP-Seq for conventional dendritic cell from cord blood, on Genome GRCh38

ChIP-Seq data for 1 sample(s) for conventional dendritic cell from cord blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

Dataset EGAD00001002948

BLUEPRINT September 2016, ChIP-Seq T-cell Acute Lymphocytic Leukemia from capillary blood, on Genome GRCh38

ChIP-Seq data for 4 sample(s) T-cell Acute Lymphocytic Leukemia from capillary blood, on Genome GRCh38. 7 run(s), 7 experiment(s), 7 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

Dataset EGAD00001002952

BLUEPRINT September 2016, ChIP-Seq for memory B cell from venous blood, on Genome GRCh38

ChIP-Seq data for 1 sample(s) for memory B cell from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

Dataset EGAD00001002950

BLUEPRINT September 2016, ChIP-Seq Acute Lymphocytic Leukemia for precursor B cell from venous blood, on Genome GRCh38

ChIP-Seq data for 1 sample(s) Acute Lymphocytic Leukemia for precursor B cell from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

Dataset EGAD00001002949

TARGET-seq+ single-cell genotyping

Single-cell genotyping data for bone marrow samples from 9 cases with clonal hematopoiesis and 1 control sample. The TARGET-seq+ protocol was used to generate plate-based 3' transcriptome data. For details on cell sorting and the TARGET-seq+ protocol see the methods section of the manuscript. One FASTQ file is provided per cell. Cells are named with their plate and well IDs and the subject ID. Empty wells (no-cell controls) are named "blank". Corresponding transcriptome files use the same naming with the "_transcriptome" suffix.

Dataset EGAD00001011150

Genome-wide DNA-methylation assessment by MethylCap-seq and Infinium HumanMethylation450 BeadChips: an independent large-scale comparison

DNA-methylation is an important epigenetic feature in health and disease. Two cost-efficient genome-scale methodologies to assess DNA-methylation are MethylCap-seq and Illumina's Infinium HumanMethylation450 BeadChips (HM450). However, objective information regarding the best-suited methodology for a specific research question is scant. Therefore, we performed a large-scale evaluation on a set of 70 brain tissue samples obtained from 65 glioblastoma and 5 non-tumoral brain tissues, using a gold standard free Bayesian modeling procedure. While conditional specificity was adequate for both approaches, conditional sensitivity was systematically higher for HM450. Also the genome-wide characteristics were compared, revealing that the HM450 probes assess less than 10% of the regions identified as methylated by MethylCap-seq. Hence the latter method may detect more potentially relevant DNA-methylation, defined by either functional location or previously reported differentially methylated candidate regions. Our results therefore indicate that – at least for the tissue under study - both methodologies are complementary, with a higher sensitivity for HM450, but a far larger genome-wide coverage for MethylCap-seq. Note that here only the relevant MethylCap-seq data is deposited, for the HM450 data we refer to GEO (GSE60274).

Study EGAS00001001191

Non-coding RNAs Activated by the Wnt/Beta-catenin Signaling Pathway in Hepatoblastoma

Hepatoblastoma (HB) is the most common pediatric liver tumor, affecting mostly children under 3 years of age. This rare tumor represents 1% of all pediatric cancers. Genetic studies have shown that HB is characterized by high frequency mutations of the CTNNB1 gene encoding beta-catenin (around 75%) and relative genomic stability. Here we have analyzed the transcriptional profile of 21 HBs compared to matched non-tumor livers by Cap Analysis of Gene Expression (CAGE), which provides accurate and quantitative profiling of all transcripts. CAGE analysis revealed strong upregulation of known Wnt target coding genes in most tumors analyzed, consistent with previous transcriptomic studies. To better define the Wnt-dependent transcriptional landscape of HB, we integrated CAGE data with TCF4 ChIP-seq data from a CTNNB1-mutated cancer cell line and with the FANTOM5 genomic coordinates of TCF/LEF binding motifs. Both TCF/LEF binding motifs and ChIP-seq peaks were strongly enriched in the immediate upstream region, not only for protein-coding genes, but also for non-coding transcripts. Among the selected 112 top Wnt target genes at FDR<1.0E-6 and fold change>8, we found clear over-representation (66%) of distant transcription start sites (TSSs) representing lncRNAs and enhancer RNAs, which raises the question of their role in HB pathogenesis. Analysis of the 112 promoters using CAGEd-oPOSSUM confirmed the predominant involvement of Tcf/Lef transcription factors, together with HNF4G, GATA2, Sox3 and Ets-related genes. Finally, the 112 Wnt target signature defined 3 tumor subclasses, T1, T2 and T3, characterized by progressive alteration of the non-coding part of the transcriptome and significant differences in clinical behavior.

Study phs001433

Mapping the epigenomic landscape of human monocytes following innate immune activation reveals context-specific mechanisms driving endotoxin tolerance

Background Monocytes are key mediators of innate immunity to infection, undergoing profound and dynamic changes in epigenetic state and immune function which are broadly protective but may be dysregulated in disease. Here, we aimed to advance understanding of epigenetic regulation following innate immune activation, acutely and in endotoxin tolerant states. Methods We exposed human primary monocytes from healthy donors (n=6) to interferon-γ or differing combinations of endotoxin (lipopolysaccharide), including acute response (2hr) and two models of endotoxin tolerance: repeated stimulations (6+6hr) and prolonged exposure to endotoxin (24hr). Another subset of monocytes was left untreated (naïve). We identified context-specific regulatory elements based on epigenetic signatures for chromatin accessibility (ATAC-seq) and regulatory non-coding RNAs from total RNA sequencing. Results We present an atlas of differential gene expression for endotoxin and interferon response, identifying widespread context specific changes. Across assayed states, only 24-29% of genes showing differential exon usage are also differential at the gene level. Overall, 19.9% (6884 of 34616) of repeatedly observed ATAC peaks were differential in at least one condition, the majority upregulated on stimulation and located in distal regions (64.1% vs 45.9% of non-differential peaks) within which sequences were less conserved than non-differential peaks. We identified enhancer-derived RNA signatures specific to different monocyte states that correlated with chromatin accessibility changes. The endotoxin tolerance models showed distinct chromatin accessibility and transcriptomic signatures, with integrated analysis identifying genes and pathways involved in the inflammatory response, detoxification, metabolism and wound healing. We leveraged eQTL mapping for the same monocyte activation states to link potential enhancers with specific genes, identifying 1,946 unique differential ATAC peaks with 1,340 expression associated genes. We further use this to inform understanding of reported GWAS, for example involving FCHO1 and coronary artery disease. Conclusion This study reports context-specific regulatory elements based on transcriptomic profiling and epigenetic signatures for enhancer-derived RNAs and chromatin accessibility in immune tolerant monocyte states, and demonstrates the informativeness of linking such elements and eQTL to inform future mechanistic studies aimed at defining therapeutic targets of immunosuppression and diseases.

Study EGAS00001007362

1M-scBloodNL

Here we present the 1M-scBloodNL study, in which we performed single-cell RNA-seq on 120 individuals of the Northern Netherlands population cohort Lifelines. For each individual peripheral blood mononuclear cells (PBMCs) were sequenced in an unstimulated condition, and after 3 and 24 hour in vitro stimulation with C. albicans (CA), M. tuberculosis (MTB) and P. aeruginosa (PA), totalling approximately 1.3 million cells. scRNA-seq was conducted with the 10X Genomics 3'-end v2 (72 libraries) and v3 (33 libraries) technology. In general, each library contains PBMCs from 8 donors and 2 different stimulation-timepoint combinations. Donors were demultiplexed using a combination of SoupOrCell (https://www.nature.com/articles/s41592-020-0820-1) and genotype information to assign the correct donor to a donor-specific cell cluster.

Dataset EGAD00001007764

Epigenetic profiles of neuroblastoma PDXs

This dataset contains bam files for ChIP-seq experiments for 6 neuroblastoma PDXs (Patient Derived Xenograft). It includes the bam files for the H3K27ac mark as well as the bam files of the corresponding input DNA for each sample.

Dataset EGAD00001003394

BLUEPRINT September 2016, ATAC-seq for tonsil, on Genome GRCh38

ATAC-seq data for 7 sample(s) from tonsil, on Genome GRCh38. 7 run(s), 7 experiment(s), 7 alignment(s). Part of BLUEPRINT (September 2016).

Dataset EGAD00001002708

BLUEPRINT September 2016, ATAC-seq for bone marrow, on Genome GRCh38

ATAC-seq data for 4 sample(s) from bone marrow, on Genome GRCh38. 4 run(s), 4 experiment(s), 4 alignment(s). Part of BLUEPRINT (September 2016).

Dataset EGAD00001002710

ctDNA mutation analysis using the SiMSen-seq approach

Mutation analysis in plasma samples with low ctDNA levels using a molecular barcoding technology, i.e. the single target approach SiMSen-seq (Simple, multiplexed, PCR-based barcoding of DNA for sensitive mutation detection using sequencing).

Dataset EGAD00001006104

Results of scRNA-seq analysis of a PBMC collected from a male with a mosaic 45,X/48,XYYY karyotype

Dataset EGAD00001008645

CLL ATAC Seq of Untreated and IBET762 treated samples

CLL PBMC cells were isolated using ficoll gradient. They have been treated with IBET762 or DMSO as solvent control and ATAC Seq has been performed on them.

Dataset EGAD00001008723

Bulk ATAC-Seq Illumina NextSeq 500 (10M reads)

Human data for chromatin accessibility (ATAC-Seq) in eight B-cell precursors: HSC, CLP, pro-B, pre-B, Immature B, Transitional B, Naive B CD5-, Naive B CD5+ cells

Dataset EGAD00001010908

CITE-seq

This dataset contains the raw sequencing data (Runs) from all of the 10x Genomics single-cell CITE-seq Experiments, as well as the demultiplexed cell-donor identities matrices which were generated with Vireo (Analysis).

Dataset EGAD00001009820

Bulk ATAC-Seq HiSeq2500 v4 reagents (100M reads)

Human data for chromatin accessibility (ATAC-Seq) in eight B-cell precursors: HSC, CLP, pro-B, pre-B, Immature B, Transitional B, Naive B CD5-, Naive B CD5+ cells

Dataset EGAD00001010909

scRNA-seq dataset for AD and Pso patients

This dataset contains scRNA-seq fastq files to the paper entitled "Single-cell profiles reveal distinctive immune response in atopic dermatitis in contrast to psoriasis". The details of experiment setup was described in the paper.

Dataset EGAD00001010106

Single Cell Dissection of the Tumour Microenvironment Reveals Dynamic Interplay Shaping the Tumour Immunity Continuum in Ovarian Cancer

Diverse tumour immune phenotypes with distinct T cell infiltration patterns result in different responses to cancer immunotherapies. However, the key determinants and biology underpinning these phenotypes remain elusive. Here, we provide a high-resolution dissection of the tumour microenvironment representative of different tumour immune phenotypes. By performing single-cell RNA sequencing (scRNAseq) of the tumour, immune, and stromal compartments from 15 ovarian cancer patients, we characterized the diverse cellular and functional phenotypes, as well as dynamic interplay within and between these components. Infiltrated and excluded tumours markedly differed from desert tumours in several tumour cell intrinsic features, including high interferon response, antigen presentation and oxidative phosphorylation. Moreover, these tumours were characterized by tumour associated macrophage (TAM)-like myeloid subsets, while desert tumours were enriched in myeloid derived suppressive cell (MDSC)-like myeloid subsets. Infiltrated and excluded tumours differed in their T cell composition and fibroblast subsets. While dysfunctional CD8+ GZMB T cells and IL1-activated fibroblasts (IL1 CAFs) were associated with infiltrated tumours, pre-dysfunctional CD8+ GZMK T cells and TGFB-activated fibroblasts (TGFB CAFs) were enriched in excluded tumours. These findings validated in bulk transcriptomic profiles of 1071 ovarian tumours and using in situ hybridization. Furthermore, our study revealed chemokine receptor-ligand interactions within and across compartments as potential mechanisms mediating immune cell infiltration, exemplified by the tumour cell-T cell crosstalk via a CXC16-CXCR6 axis, stromal-immune cell crosstalk via CXCL12/14-CXCR4 signalling, and TAM-like macrophage-T cell crosstalk through CXCR3-CXCL9/10/11 signalling. Our in-depth characterization of the tumour environment and intercellular interactions provides novel insights into potential molecular mechanisms that shape the distinct biology of tumour immune phenotypes. Our findings may inform novel therapeutic strategies for potentially shifting tumours along the immunity continuum to improve clinical benefit from cancer immunotherapies.

Study EGAS00001004935

9338 results for "cancer rna-seq"

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