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• BLUEPRINT release August 2016, Bisulfite-Seq for germinal center B cell, on genome GRCh38

  Bisulfite-Seq data for 3 germinal center B cell sample(s). 37 run(s), 4 experiment(s), 6 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002511

• BLUEPRINT release August 2016, RNA-Seq for Acute Promyelocytic Leukemia - MC2884 (4h), on genome GRCh38

  RNA-Seq data for 1 Acute Promyelocytic Leukemia - MC2884 (4h) sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002513

• BLUEPRINT release August 2016, ChIP-Seq for Acute Promyelocytic Leukemia - MC2494, on genome GRCh38

  ChIP-Seq data for 1 Acute Promyelocytic Leukemia - MC2494 sample(s). 2 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002516

• BLUEPRINT release August 2016, RNA-Seq for Chronic Lymphocytic Leukemia, on genome GRCh38

  RNA-Seq data for 7 Chronic Lymphocytic Leukemia sample(s). 7 run(s), 7 experiment(s), 7 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002518

• BLUEPRINT release August 2016, Bisulfite-Seq for CD38-negative naive B cell, on genome GRCh38

  Bisulfite-Seq data for 4 CD38-negative naive B cell sample(s). 51 run(s), 5 experiment(s), 8 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002520

• BLUEPRINT release August 2016, Bisulfite-Seq for CD14-positive, CD16-negative classical monocyte, on genome GRCh38

  Bisulfite-Seq data for 6 CD14-positive, CD16-negative classical monocyte sample(s). 86 run(s), 6 experiment(s), 12 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002523

• BLUEPRINT release August 2016, ChIP-Seq for Acute Promyelocytic Leukemia - CTR, on genome GRCh38

  ChIP-Seq data for 3 Acute Promyelocytic Leukemia - CTR sample(s). 22 run(s), 21 experiment(s), 21 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002490

• BLUEPRINT release August 2016, Bisulfite-Seq for CD8-positive, alpha-beta T cell, on genome GRCh38

  Bisulfite-Seq data for 4 CD8-positive, alpha-beta T cell sample(s). 57 run(s), 5 experiment(s), 8 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002496

• DAC for Whole Genome Sequencing Expands Diagnostic Utility and Improves Clinical Management in Pediatric Medicine

  Dac EGAC00001000419

• Data access policy for PDTX Breast Cancer RNA-seq data from Ros et al (2020)

  Dac EGAC00001001620

• DAC for "Detection of Gene Fusions using Targeted Next-Generation Sequencing – a Comparative Evaluation"

  Dac EGAC00001001905

• Data Access Committee for study Genetics of Preeclampsia at High Altitudes

  Dac EGAC00001002097

• DAC for YCC Sarcoma

  Access can be granted by contacting Hyo Song Kim (hyosong77@yuhs.ac).

  Dac EGAC50000000046

• Identification of IQCH as a calmodulin-associated protein required for sperm motility in humans

  Study EGAS00001007423

• DAC - A standardised framework for robust fragmentomic feature extraction from cell-free DNA sequencing data

  Dac EGAC00001003530

• Human glioblastoma single cell DAC (Linnarsson)

  DAC for human glioblastoma single cell sequencing samples

  Dac EGAC50000000575

• Human developing meninges single cell DAC (Linnarsson)

  DAC for human developing meninges single cell sequencing

  Dac EGAC50000000576

• Asan Medical Center Data Access Committee

  Asan Medical Center Data Access Committee for BRISK study.

  Dac EGAC50000000733

• DAC SysMed

  Data access control for datasets submitted by SysMed

  Dac EGAC50000000089

• DAC for Genetic and Microenvironmental Analysis of PTCL at Department of Hematology, University of Tsukuba

  Dac EGAC50000000600

• DAC for "H3K27me3-mediated epigenetic repression regulates neuroblastoma development and contributes to biological heterogeneity"

  Dac EGAC00001003620

• Circulating tumor cells for comprehensive and multiregional non-invasive genetic characterization of multiple myeloma

  Study EGAS00001004288

• EGAD00000000027

  eQTL data for European newborns

  Dataset EGAD00000000027

• Genome sequencing in monozygotic twins discordant for Mayer-Rokitansky-Küster-Hauser syndrome

  Study EGAS00001006371

• Exome reads

  Exome sequencing for 2 infertile brothers

  Dataset EGAD00001003193

• Exome data for PDXs

  Exome data of PDX models.

  Dataset EGAD00001001863

• NIDDM-Atherosclerosis Study (NIDDM-Athero)

  The NIDDM-Atherosclerosis Study, funded by NHLBI, was designed as a family study to examine the genetic basis of subclinical atherosclerosis and diabetes in Hispanic families. Family members of probands with T2D were recruited in the Los Angeles area. The baseline examination of the cohort included the euglycemic hyperinsulinemic clamp test from which the two key phenotypes were obtained: insulin sensitivity (M) and metabolic clearance rate of insulin (MCRI). Genome-wide genotyping was obtained under separate funding by NIDDK as a part of the GUARDIAN (Genetics Underlying Diabetes in Hispanics) Consortium.

  Study phs001130

• Transcriptomic profiling of fragile X syndrome unmethylated full mutation carriers

  Total RNA sequencing of fibroblasts from two unrelated FMR1 unmethylated full mutation carriers, a fragile X patient and a control individual. The existence of rare, unmethylated full mutation carriers who carry the mutation that causes fragile X syndrome but do not gain methylation at the locus offers a rare opportunity to study the mechanisms underlying fragile X syndrome. This study aims to compare the transcriptomes of these four individuals in order to elucidate the mechanism behind the methylation a the FMR1 CGG repeat expansion that causes Fragile X syndrome.

  Study EGAS50000000647

• Whole genome sequencing of colon organoid cultures with artificially induced oncogenic mutations

  Using the CRISPR-Cas9 genome editing system, various oncogenic mutations were introduced in the genome of normal adult stem cells derived from the colon. The resulting clonal cultures were subjected to whole genome sequencing. In addition, the cultures were transplanted in a mouse and the resulting primary and metastatic tumors were also subjected to whole genome sequencing. The initial bulk culture, which was used to generate the mutations, was also whole genome sequenced and served as a reference sample to filter germline variants.

  Study EGAS00001001969

• Small RNA sequencing of endometrial cancer patients with samples collected prior to diagnosis and controls

  This dataset contains unpaired FASTQ files of 316 endometrial cancer cases and 316 matched controls representing circulating RNAs. RNA count files are provided as the output of sncRNA pipeline and represent 12 RNA types (isomiR, lncRNA, precursor miRNA, miRNA, miscRNA, mRNA, piRNA, scaRNA, snoRNA, snRNA, tRF, and tRNA). We also provide metadata of the samples.

  Dataset EGAD50000000391

• Genomic characterization of hepatocellular carcinoma in Hispanic patients

  The genomic DNA was extracted from paired tumor and adjacent non-tumor samples of 27 Hispanic HCC patients. The TruSeq Rapid Exome Library Prep kit (Illumina, CA) was used to capture the coding regions of the human genome. The 100 bp paired-end sequencing of every 6-plex whole exome library pool was performed on an Illumina HiSeq 3000 system according to the manufacturer’s recommended protocol to achieve an average coverage of ~100X. The paired-end reads were aligned to the human reference genome (hg19) with decoy sequences (as used in the 1000 Genomes Project) using BWA software. The duplicate reads were marked and removed using Picard and SAMtools, respectively. Local realignment around insertions/deletions (indels) and base quality recalibration were performed using GATK.

  Study EGAS00001007431

• Genome-wide data from Agta hunter-gatherers in Philippines

  To investigate the relationship between host genetics and the oral microbiome composition of Agta hunter-gatherers from the Philippines, we genotyped the Agta population (hunter-gatherers from Philippines) together with BaYaka (hunter-gatherers from Congo) and Palanan farmers (neighbouring population of the Agta).

  Study EGAS00001005315

• MDD2000AFFY

  Sub-study QI: 941 cases of Major Depressive Disorder (MDD) from the Queensland Institute of Medical Research (QIMR), Australia Sub-study VU: 127 MDD cases from The Netherlands Study of Anxiety and Depression (NESDA) (http://www.nesda.nl) and The Netherlands Twin Registry (NTR) (http://www.tweelingenregister.org) based at the VU Amsterdam, The Netherlands. Sub-study ED: 373 MDD cases from the University of Edinburgh, UK.

  Study phs000658

• BulkRNAseq - Notch Signaling Maintains a Progenitor-Like Subclass of Hepatocellular Carcinoma

  To identify the Notch signaling components expressed in both the human cancer cells and mouse stromal cells that typically comprise PDX tumors, we performed bulk RNA sequencing. Our results demonstrate that a JAG1-NOTCH2 signaling axis within the human cancer cell population drives the Notch dependency in the super-responder models, with NOTCH2 serving as the functionally relevant receptor.

  Study EGAS50000000515

• Archive growth Statistics

  EGA Statistics Bibliography Growth Community Archive Distribution Catalogue In this section, we expose the overall volume of data available to download and the different archived file types. EGA Archive growth in size and number of files The below figure represents the EGA archive growth in size (TB) and number of files. EGA Archive Growth per year lineChart('ega-archive-growth', 'https://stats.ega-archive.org/growth/archive', ['Volume (TB)'], ['T']) Archive files The below figure represents on a initial level, the percentage of archived files by data technology. The second level, acessible by clicking in the required extension, displays the number of files by extension archived in the ega archive. Please click over the extension to learn more about the files. EGA Archived Files barChart('ega-archived-files', 'https://stats.ega-archive.org/extensions', false ,'', true)

  Documentation about/statistics/archive

• Gene expression adaptation of metastases to their host tissue

  The adaptation of metastatic cells to their host tissue critically determines the pathogenicity of a cancer and therefore patient survival. Yet, it remains elusive to what extent the host environment drives gene expression programs in metastatic cells. Here we identify adaptive mechanisms that enable metastases to establish themselves in a novel tissue context. We performed single-cell RNA-sequencing on malignant and benign tissue samples from untreated donors with colorectal adenocarcinoma and liver metastasis to deduce tissue adaptive expression patterns. A novel computational approach identified genes and pathways that consistently adapted to the host tissue at the transition from the primary tumor to the paired metastasis across donors. This analysis revealed that the majority of expression changes in the metastasis reflect an expression signature reminiscent of benign liver epithelial cells. Cellular processes adapting to the liver environment include basic cellular functions such as energy metabolism, as well as tissue-specific pathways such as the regulation of lipid metabolism by PPAR-α. These adaptations potentially increase the pathogenicity of the metastatic cells and may provide new therapeutic strategies.

  Study EGAS50000000817

• Whole exome sequencing data from non-small-cell lung cancer patients receiving immunotherapy prognosis

  The plasma samples and white blood cell samples were collected from 30 non-small-cell lung cancer patients and 3 healthy individuals. The solid tumor biopsy samples from 14 patients (a subset of the 30 patients) were collected. The cfDNA was extracted from their plasma samples using the QIAamp circulating nucleic acid kit from QIAGEN (Germantown, MD). The cfDNA WES library was constructed with the SureSelect XT HS kit from Agilent Technologies (Santa Clara, CA) according to the manufacturer’s protocol. In brief, 10ng of cfDNA was used as input material. After end repair/dA-tailing of cfDNA, the adaptor was ligated. The ligation product was purified with Ampure XP beads (Beckman-Coulter, Atlanta, GA) and the adaptor-ligated library was amplified with index primer in 10-cycle PCR. The amplified library was purified again with Ampure XP beads, and the amount of amplified DNA was measured using the Qubit 1xdsDNA HS assay kit (ThermoFisher, Waltham, MA). 700-1000 ng of DNA sample was hybridized to the Agilent SureSelect Human All Exon V6 (Agilent) capture library and pulled down by streptavidin-coated beads. After washing the beads, the DNA library captured on the beads was re-amplified with 10-cycle PCR. The final libraries were purified by Ampure XP beads. The library concentration was measured by Qubit, and the quality was further examined with Agilent Bioanalyzer before the final step of 2x150bp paired-end sequencing on the Illumina HiSeq X10 platform (Illumina) at an average coverage of 200. Whole-exome capture libraries of genomic DNA of the 30 non-small cell lung cancer patients were constructed via Roche SeqCap EZ Exome V3 (Roche); whole-exome capture libraries of genomic DNA of the 3 healthy individuals were constructed via Agilent SureSelect Human All Exon V6 (Agilent). Enriched exome libraries were sequenced on the Illumina HiSeq 3000 platform (Illumina) to generate 2x100bp paired-end reads at an average coverage of 200.

  Dataset EGAD00001006096

• Single cell RNA seq of the developing human embryo brain

  The study aims at identifying the cell types and lineages of the developing human brain.

  Study EGAS00001004107

• Reference_DNA_standards_for_GCLP_pipeline

  The use of reference DNA standards generated from cancer cell lines sequenced in the Cancer Genome Project to establish the sensitivity, specificity, accuracy and reproducibility of the WTSI GCLP sequencing pipeline

  Study EGAS00001001173

• The Druze analysis group

  To comprehensively characterize the genetic structure of the Druze population, we recruited and genotyped 40 parent-offspring trios from the Upper Galilee in Israel and the Golan Heights, attempting to capture different extended families (clans) across various geographical locations.

  Study EGAS00001000963

• Data access policy for PDTX Breast Cancer data from Bruna et al (2016), Cell.

  Dac EGAC00001000540

• CIR-RIMLS committee on data access to Immunological mechanisms for celiac disease database

  Dac EGAC00001000557

• DAC for "A Functional Network of Gastric-Cancer-Associated Splicing Events Controlled by Dysregulated Splicing Factors"

  Dac EGAC00001000675

• DAC for Hungarian human exome team (Department of Medical Biology, University of Szeged, Hungary)

  Dac EGAC00001000838

• DAC for study: "Circulating tumour DNA abundance and potential utility in de novo metastatic prostate cancer"

  Dac EGAC00001001099

• Control iPSC lines with clinically annotated genetic variants for versatile multi-lineage differentiation Committee (part II)

  Dac EGAC00001001332

• Integration of intra-sample contextual error modeling for improved detection of somatic mutations

  Study EGAS00001003806

• Evaluating CRISPR-based Prime Editing for cancer modeling and CFTR repair in organoids

  Study EGAS00001005358

• Stage-1 GWAS

  Summary statistics from Stage-1 GWAS for blood pressure phenotypes

  Dataset EGAD00010001569

• Quad samples for study EGAS00001001023

  Dataset EGAD00001001126