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• Stanford Data Access Committee for Multi-Region WES of Metastatic Colorectal Cancer

  Dac EGAC00001001164

• DAC for the study of tumor-derived somatic mutation detection in cfDNA

  Dac EGAC00001001569

• Nicola Murray Centre for Ovarian Cancer Research Data Access Committee

  Dac EGAC00001001588

• Cancer Clinical Research Trust DAC for WES of HER2+ metastatic cancer samples

  Dac EGAC00001001632

• Data Access Commitee of the Princess Maxima Center for Pediatric Oncology

  Dac EGAC00001001948

• Data access committee for Gut microbiome of BA patients and normal controls

  Dac EGAC00001002146

• "DAC for RNAseq from regions of insitu and invasive human mammary ductal disease"

  Dac EGAC00001002538

• Chromatin Profiles in PRAD - Englander Institute for Precision Medicine - Weill Cornell Medicine

  Dac EGAC00001002559

• Single cell multi-omics group for somatic structural variation in human blood lineages

  Dac EGAC00001002852

• EGAD00010000831

  BLUEPRINT EpiMatch: harnessing epigenetics for haematopoietic stem cell transplantation

  Dataset EGAD00010000831

• irish_fineSTRUCTURE

  SNP data for 991 Irish individuals

  Dataset EGAD00010001479

• DNA Methylation data for EGAS00001002592

  Islet_HumanMethylation450K_ThurnerEtAl

  Dataset EGAD00010001695

• DAC for Tuebingen-Stuttgart cohort

  Dac EGAC00001000317

• Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Jackson Heart Study (JHS)

  Study phs002907

• A multi-center genome-wide association study for nasopharyngeal carcinoma

  Study EGAS00001006062

• DAC for Clonal driver neoantigen loss under EGFR TKI and immune selection pressures

  Dac EGAC00001003522

• The MALT1 Locus and Peanut Avoidance in the Risk for Peanut Allergy

  The LEAP study was a randomized controlled clinical trial in children at increased risk for peanut allergy, in which intervention using dietary introduction of peanut protein beginning in the first 4 to 11 months of life, continued until age 5 years, significantly decreased the frequency of peanut allergy later in childhood and modulated the immune response to peanuts. All subject phenotype data will be hosted on ITN Trial Share under the LEAP study.

  Study phs001851

• NHLBI TOPMed: Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Project: Cardiovascular Health Study

  Participants from the Cardiovascular Health Study (CHS), a large population-based longitudinal cohort study (phs000287), have been included in the TOPMed project. Whole genome sequencing will be performed to contribute to multiple analyses, including cardiovascular disease risk factors, subclinical disease measures, the occurrence of myocardial infarction (MI) and stroke, and analyses of venous thromboembolism (VTE).Comprehensive phenotypic and pedigree data for study participants are available through dbGaP phs000287.

  Study phs001368

• Identification of Novel Therapeutic Targets for Calcific Aortic Valve Stenosis Using Integrative Genomics

  In order to identify novel therapeutic targets for calcific aortic valve stenosis, we have generated a large transcriptomic dataset from RNA sequencing of human aortic valve tissues from 500 individuals undergoing aortic valve replacement or heart transplant at the Institut universitaire de cardiologie et de pneumologie de Québec – Université Laval (QUEBEC-CAVS-RNA). This dataset represents a unique resource to understand the molecular mechanisms underlying aortic valve diseases.

  Study phs003541

• DNA methylation database for gynecological cancer detection, classification and assay development

  DNA methylation changes are associated with cancer the best predictor of the presence of cancer. In order to detect and classify gynecological cancer, we performed MeD-seq to generate DNA methylation profiles of vulvar, cervical, endometrial, fallopian tube and ovarian cancers and their associated healthy tissues. DNA methylation profiles were used to find general cancer, regional cancer and specific cancer biomarkers that can be used for cancer detection, classification and treatment monitoring.

  Study EGAS50000000417

• Oesophageal adenocarcinoma scRNAseq from LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19)

  This dataset contains single-cell RNA-seq generated from the LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19) and additional donors with Barrett's oesophagus using the 5' Single Cell Gene Expression assay from 10x Genomics. Samples were generated from oesophageal tumours, Barrett's oesophagus, and normal oesophagus and gastric tissues, with the aim of generating a reference atlas for cell types found in normal and disease-associated tissue states in the upper GI tract. This reference atlas was used as the basis for a deconvolution workflow to estimate the cell composition of bulk transcriptomes from these tissues, and to assess cell type-specific expression patterns of potential predictive biomarkers for immunochemotherapy regimens in this setting.

  Dataset EGAD00001009401

• Transcriptome-Wide Association Study (TWAS) to Identify Susceptibility Genes for Colorectal Cancer

  This study included genotype data from 420 study participants of East Asian descent, along with RNA-seq (n=300) and small RNA seq data (n=400) generated from their colorectal tissue samples. We used the transcriptome data and genotype data from these individuals to build a prediction model for each coding gene and long non-coding RNA, and perform a Transcriptome-Wide Association Study (TWAS) of colorectal cancer in East Asian populations.

  Study phs002813

• Indonesian Microbiome Ecology and Evolution v1 (raw data)

  This dataset comprises 124 human faecal samples collected across Indonesia between 2015 and 2021, together with 6 controls. It was collected to study patterns of human microbiome variation across Indonesia’s diverse geography and lifestyles, and to generate the Indonesian Microbiome Ecology and Evolution (IndoMEE) metagenome-assembled genome (MAG) reference database. The dataset consists of 250 bp paired-end metagenomic reads from 124 faecal samples acquired from 116 individuals, at ca. 10.6 Gb / sample, together with 2 positive controls (ZymoBIOMICS Microbial Community DNA Standard by Zymo Research Cat# D6305), and 4 negative controls (for sampling: Blank, for extraction: Buffer EB by Qiagen Cat# 19086, for library prep: Nuclease Free Water by Ambion-Invitrogen Cat# AM9937). Library preparation was carried out using Illumina's TruSeq DNA Nano DNA kit, and sequencing was performed on the Illumina NovaSeq 6000 platform.

  Dataset EGAD50000001399

• A prospective trial comparing adaptive long-read sequencing and short-read genome sequencing for genetic diagnosis of cerebellar ataxia

  This study evaluated the effectiveness of long- and short-read sequencing as diagnostic tools for CA. We recruited 110 individuals (48 females, 62 males) with a clinical diagnosis of CA. Short-read genome sequencing (SR-GS) was performed to identify pathogenic RE and also non-RE variants in 356 genes associated with CA. Long-read adaptive sequencing (LR-AS) was performed to identify pathogenic RE in 67 genes.

  Study EGAS50000000573

• Benchmark Dataset for Somatic Mutation Calling in Cell-Free DNA

  This study provides a comprehensive benchmarking resource for somatic variant detection in cell-free DNA (cfDNA) from cancer patients. Longitudinal plasma samples from colorectal and breast cancer cohorts were selected to create patient-matched dilution series spanning ultra-low to high circulating-tumour-DNA (ctDNA) fractions, while preserving each individual’s germline and clonal haematopoiesis background. Deep whole-genome sequencing (150×) and ultra-deep whole-exome sequencing (2,000×) generated a reference call set of ~37,000 single-nucleotide variants and ~58,000 insertions/deletions. These data enabled systematic evaluation of nine somatic variant callers across variable ctDNA levels and sequencing depths, and were further used to explore machine-learning–guided parameter tuning. The resulting dataset offers an openly accessible framework for developers and clinicians to assess and optimize somatic variant calling in liquid biopsy applications.

  Dataset EGAD50000001870