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• 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

• Measurement of the Male Germline Mutation Rate Using Sequential Sperm Samples

  We recalled 23 sperm donors with prior banked samples to provide a new sperm sample. The old and new sequential sperm samples were then profiled by high-fidelity duplex sequencing to measure individual-specific mutation rates and patterns. We also performed deep whole-genome sequencing of sequential sperm samples from two individuals followed by targeted validation, which measured remarkably stable mosaicism of clonal mutations that likely arose during embryonic and germline development.

  Study phs003716

• Whole-exome sequencing profiling of patients with metastatic prostate cancer at VHIO

  Metastatic prostate cancer (mPC) is enriched for homologous recombination repair (HRR) gene alterations, which have prognostic and predictive value. Routine clinical implementation of next-generation sequencing (NGS) is still limited. We investigated the association between genomic and functional loss of HRR, using NGS and a RAD51 immunofluorescence (RAD51-IF) iprimary or metastatic biopsies from patients with stage IV prostate cancer. Whole-exome sequencing was pursued for paired tumor-normal samples.

  Study EGAS50000000736

• MOSAIC - Multi-Omics Spatial Atlas In Cancer

  MOSAIC is a collaborative initiative founded by Owkin, Lausanne University Hospital (CHUV), Charité Universitätsmedizin Berlin, University Hospital Erlangen (UKER), Gustave Roussy Institute in Paris, and University of Pittsburgh. The goal of MOSAIC is to build the largest collection of spatial omics data in cancer. By integrating comprehensive high quality clinical annotations with advanced deep profiling techniques, MOSAIC aims to uncover novel cancer subtypes and identify key drug targets and biomarkers within them.

  Study EGAS50000000689

• Synthetic - GDI synthetic data

  Synthetic - The Genomic Data Infrastructure (GDI) project is enabling access to genomic and related phenotypic and clinical data across Europe. It is doing this by establishing a federated, sustainable and secure infrastructure to access the data. In support of FAIRness in data sharing, this dataset is made freely available under the Creative Commons Licence (CC-BY). Please ensure the GDI project (funding: EC H2020 under grant agreement number 101081813) is acknowledged.

  Study EGAS50000000678

• Single-cell transcriptomic analyses of peripheral blood mononuclear cells, peritoneal fluid, and peritoneal metastases from patients with colorectal cancer

  The data published here contains single-cell RNA- sequencing (scRNAseq) on peripheral blood mononuclear cells (PBMC), peritoneal fluid (PF), and peritoneal metastases (PM). PBMC, PF and, where possible, PM was acquired from patients with colorectal cancer (CRC) and subjected to 3' scRNAseq using the 10X Genomics (Chromium Single Cell 3’ Reagent). Sequencing was performed in a paired-ended fashion on either the HiSeq4000 or the NovaSeq6000.

  Study EGAS50000000173

• Single-cell RNA-sequencing and cellular indexing of transcriptomes and epitopes of peripheral blood mononuclear cells and peritoneal fluid from patients with achalasia

  The data published here contains cellular indexing of transcriptomes and epitopes (CITE-seq) and single-cell RNA- sequencing (scRNAseq) data on patients with achalasia. Paired PBMC and PF were subjected to 3' scRNAseq and CITE-seq, respectively. All single-cell data was generated using the 10X Genomics (Chromium Single Cell 3’ Reagent) and sequenced in a paired-ended fashion on the NovaSeq6000.

  Study EGAS50000000174

• Genomic profiling of fragile X syndrome unmethylated full mutation carriers

  Whole genome sequencing of two unrelated FMR1 unmethylated full mutation carriers. 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 investigate the genomic variants in these individuals alongside transcriptomic data to elucidate underlying genomic variants behind transcriptomic differences observed in UFM individuals.

  Study EGAS50000000648

• Integrated targeted deep sequencing reveals unique tissue-of-origin and donor cell-free DNA signatures in transplant recipients

  We have developed a targeted deep methylation sequencing assay that integrates cell-free DNA (cfDNA) tissue-of-origin analysis with donor-derived cfDNA quantification to non-invasively monitor transplant health. In this study, liver and kidney transplant recipients were assessed in conjunction with healthy controls to characterize the dynamic patterns of cfDNA release and clearance, and to identify distinct tissue injury signatures throughout the transplant journey.

  Study EGAS50000000987

• Total RNA expression in benign ovarian and malignant ovarian tumours

  This study investigates the total RNA expression profiles of fresh-frozen ovarian tumors, providing a comprehensive analysis of 112 samples from 111 women in Sweden, two samples being replicates. The dataset includes 18 benign and 94 malignant tumours, collected as part of the U-CAN initiative from Uppsala Biobank. The sequencing data offers valuable insights into ovarian tumour biology and can be used to enhance understanding of tumour classification and molecular characteristics.

  Study EGAS50000001045