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• Germline Sequencing for Aggressive Prostate Carcinoma

  This study aims to elucidate the genetic determinants of susceptibility to aggressive prostate carcinoma. To this end, germ line whole exome sequence has been generated from patients with aggressive prostate cancer. Whole genome sequence for a representative subset of tumors from patients whose cancer was resistant to primary therapy is included as well. This deep genomic interrogation will allow the identification of rare, functionally disruptive variants that may play a role in disease progession and response to treatment.

  Study phs000661

• Extracellular microRNA Biomarkers for Diagnostic and Prognostic Assessment of Preeclampsia at Triage

  This study is comprised of samples from 123 donors (71 cases and 52 controls) undergoing evaluation for preeclampsia. All samples were collected between 20 and 40 weeks of gestation. Small RNA sequencing was done on serum RNA obtained from donors. We were able to identify 3 bivariate extracellular miRNA biomarkers that can enable early diagnosis of preeclampsia. The raw fastq small-RNA sequencing fastq files will be submitted to dbGaP.

  Study phs003169

• 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

• WES Breast Patient-derived Tumor Organoid

  This dataset includes 18 Whole Exome Sequencing (WES) samples from 5 subjects. WES is performed on a matched pair of case/control samples, e.g., tumor/control or organoid/control. For each patient, the same control sample is used for the analysis of tumor and organoid samples. The sample name structure identifies the type of sample: <subjectId>_[TON][12]_[Case|Ctrl]_EX2; where T, O, and N refer to Tumor tissue, Organoid, and control sample, respectively. The number 1 or 2 refers to the specific tissue, and Case and Ctrl indicate a tumor tissue (or organoid) and a control sample, respectively. For example, ICSBCS007_T1_Case_EX2 is the first tumor tissue of subject ICSBCS007; ICSBCS007_O1_Case_EX2 is the tumor organoid derived from that tumor sample, and ICSBCS007_N1_Ctrl_EX2 is the matching control sample. More information can be found in the sample information table.

  Dataset EGAD50000000961

• 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