Search Results - EGA European Genome-Phenome Archive

SGCC GASCAD-II dataset

The GASCAD-II dataset from the Singapore Gastric Cancer Consortium includes paired tumor-blood whole exome sequencing data for 209 gastric cancer (GC) patients, along with whole transcriptome sequencing data for 125 GC samples. Whole exome sequencing was conducted using Agilent SureSelect Human All Exon V6 kits. For RNA sequencing, total RNA was isolated using the RNeasy Mini Kit, and libraries were prepared with the TruSeq Stranded Total RNA with Ribo-Zero Gold protocol (Illumina). Aligned BAM files for both exome and RNAseq data are included in this dataset

Dataset EGAD00001015433

Dataset for manuscript titled: Spatial Intra-Tumour Heterogeneity and Treatment-Induced Genomic Evolution in Oesophageal Adenocarcinoma: Implications for Prognosis and Therapy

Dataset EGAD00001015373

NINDS-Genome-Wide Genotyping in Parkinson's Disease: First Stage Analysis and Public Release of Data

Epidemiological studies have estimated a cumulative prevalence of PD of greater than 1 per thousand. When prevalence is limited to senior populations, this proportion increases nearly 10-fold. The estimated genetic risk ratio for PD is approximately 1.7 (70% increased risk for PD if a sibling has PD) for all ages, and increases over 7-fold for those under age 66 years. The role for genes contributing to the risk of PD is therefore significant. This study utilized the well characterized collection of North American Caucasians with Parkinson's disease, and neurologically normal controls from the sample population which are banked in the National Institute of Neurological Disorders and Stroke (NINDS Repository) collection for a first stage whole genome analysis. Genome-wide, single nucleotide polymorphism (SNP) genotyping of these publicly available samples was originally done in 267 Parkinson's disease patients and 270 controls, and this has been extended to include genome wide genotyping in 939 Parkinson's disease cases and 802 controls. The NINDS repository was established in 10-2001 towards the goal of developing standardized, broadly useful diagnostic and other clinical data and a collection of DNA and cell line samples to further advances in gene discovery of neurological disorders. All samples, phenotypic, and genotypic data are available to the research community including to academics and industry scientists. In addition, well characterized neurologically normal control subjects are a part of the collection. This collection formed the basis of this first stage study by Fung et al., and the expanded study by Simon-Sanchez et al. The genotyping data was generated and provided by the laboratory of Dr. Andrew Singleton NIA, and Dr. John Hardy NIA (NIH Intramural, funding from NIA and NINDS). Important links to apply for individual-level data Data Use Certification Requirements (DUC) Apply here for controlled access to individual level data Participant Protection Policy FAQ

Study phs000089

Population Architecture using Genomics and Epidemiology (PAGE): Multiethnic Cohort (MEC)

The Multiethnic Cohort (MEC) has established a large biorepository of blood and urine (N=67,000) and cryopreserved lymphocytes (N=15,000) linked to extensive, prospectively collected risk factors (e.g., diet, smoking, physical activity), biomarkers and clinical data for five racial/ethnic groups. This cohort study of over 215,000 men and women in Hawaii and California is unique in that it is population-based and includes large representations of older adults (45-75 yrs at baseline) for five US racial/ethnic groups (Japanese Americans, African Americans, European Americans, Latinos and Native Hawaiians) at varying risks of chronic diseases. Within the PAGE investigation, the MEC proposes to study: 1) diseases for which we have DNA available for large numbers of cases and controls (breast, prostate, and colorectal cancer, diabetes, and obesity); 2) important cancers that are less common (e.g., lung, pancreas, endometrial cancers, NHL) but for which we propose to pool our data with other funded groups; 3) common traits that are risk factors for these diseases (e.g., body mass index/weight, waist-to-hip ratio, height) and 4) relevant disease-associated biomarkers (e.g., fasting insulin and lipids, steroid hormones). The specific aims are: 1) To determine the population-based epidemiologic profile (allele frequency, main effect, heterogeneity by disease characteristics) of putative causal variants in the five racial/ethnic groups in the MEC; 2) for variants displaying effect heterogeneity across ethnic/racial groups, we will utilize differences in LD to identify a more complete spectrum of associated variants at these loci; 3) investigate gene x gene and gene x environment interactions to identify modifiers; 4) examine the associations of putative causal variants with already measured intermediate phenotypes (e.g., plasma insulin, lipids, steroid hormones); and 5) for variants that do not fall within known genes, start to investigate their relationships with gene expression and epigenetic patterns in small genomic studies. This study is part of the Population Architecture using Genomics and Epidemiology (PAGE) study phs000356.

Study phs000220

OLD DATA FILES FOR SJMB - Superseded by EGAD00001001864

Dataset EGAD00001000269

RNAseq for 8 PDX

RNAseq for #111, #1177, #206, #201, #29, #931, WO-19, WO-2

Dataset EGAD50000000116

Preeclampsia InterPregGen Consortium: GWAS meta-analysis summary statistics for European fetal preeclampsia cases versus controls and GWAS genotype data for European fetal preeclampsia cases

Study EGAS00001001048

sc-DECISION

Data derived from PBMC and blood samples for the single cell and bulk RNAseq analysis for the sc-DECISION paper. https://doi.org/10.1101/2025.02.04.25321370

Dac EGAC50000000642

Pulldown_DNA_methylation_study_v2

Pilot study to set up sequencing protocols for targeted pulldown methylation profiling

Study EGAS00001000979

McGill EMC Release 4 for assay "H3K27ac"

Dataset EGAD00001001298

Dataset for "Genomic landscape of oral cancers" (Illumina WGS)

Dataset EGAD00001004356

McGill EMC Release 4 for assay "H3K9me3"

Dataset EGAD00001001299

McGill EMC Release 4 for assay "H3K4me1"

Dataset EGAD00001001296

WGS data for Glioblastoma (EGAS00001003953, H016)

Whole genome sequencing data for 20 human glioblastoma patients.

Dataset EGAD00001006545

McGill EMC Release 4 for assay "H3K36me3"

Dataset EGAD00001001295

Dataset for "Genomic landscape of oral cancers" (CGI WGS)

Dataset EGAD00001004339

BLUEPRINT: DNaseI-seq for monocytes

DNaseI-seq for monocytes

Dataset EGAD00001000674

McGill EMC Release 4 for assay "H3K4me3"

Dataset EGAD00001001297

DATA FILES FOR Histone-NSD2_RNASeq

Dataset EGAD00001000655

DATA FILES FOR GRUBER SJAMLM7 RNASEQ

Dataset EGAD00001003135

PBMC_dual_10X_kit

Dual snRNAseq and ATACseq of replicate PBMC samples for 10X beta testing.

Study EGAS00001004834

McGill EMC Release 4 for assay "H3K27me3"

Dataset EGAD00001001294

WTCCC2 case-control study for Ulcerative Colitis

WTCCC2 project genome-wide case-control association study for Ulcerative Colitis (UC) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

Study EGAS00000000084

Data from Shea et al Can Research 2025

This dataset contains single cell RNA sequencing (192 fastq files for 59 samples), whole exome sequencing (20 BAM files -hg38- for 20 samples) and bulk RNA sequencing (138 paired-end fastq files and 17 single-end fastq files for 8 samples)

Dataset EGAD50000001334

FLT3 is genetically essential for ITD-mutated leukemic stem cells but dispensable for human HSCs

bulk RNA sequencing of AML patients It contains 18 samples from primary AML patients. Half of the samples are control samples and half of the samples are FLT3-ITD knock-out (edited for the FLT3-ITD mutation). It is using Illumina high-throughput technology

Dataset EGAD50000000636

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