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• NIPT samples for systematic evaluation of NIPT aneuploidy detection software tools

  This dataset contains two sets of samples. The reference sample set consists of a total of 669 samples that had been reported previously to be euploid by the NIPTIFY screening test. The validation sample set is based on a previously published validation study by Zilina et al. (1), consisting of 423 samples, of which 259 were high-risk pregnancies that had undergone diagnostic invasive prenatal analysis (1). All samples were sequenced with Illumina NextSeq 500 platform, producing 85 bp single-end reads with an average per-sample coverage of 0.32× at the University of Tartu, Institute of Genomics Core Facility, according to the manufacturer’s standard protocols, as described previously (1). This study was performed with the approval of the Research Ethics Committee of the University of Tartu (#315/T-13). 1. Zilina O, Rekker K, Kaplinski L, Sauk M, Paluoja P, Teder H, et al. Creating basis for introducing non‐invasive prenatal testing in the Estonian public health setting. Prenat Diagn [Internet]. 2019 Dec 6;39(13):1262-8. Available from: https://onlinelibrary.wiley.com/doi/abs/10.1002/pd.5578

  Dataset EGAD00001007712

• Genetic drivers of epigenetic and transcriptional variation of human immune responses to infection (RNA-seq, ATAC-seq and ChIPmentation)

  RNA-seq, ATAC-seq and ChIPmentation data from monocyte-derived macrophages that were infected with Influenza A virus strain PR8WT, or a matching non-infected control.

  Dataset EGAD00001008422

• A Tumour Organoid Biobank for Mapping Cancer Cell Vulnerabilities - WGS

  Whole genome sequencing data from cancer patient-derived organoids and their matched tumour tissue samples. Part of a study to include genomic and transcriptomic sequencing data, along with CRISPR screening data from cancer patient-derived organoids and matched tumour tissues. Some organoids were developed as part of the Human Cancer Models Initiative (HCMI) in collaboration with Cancer Research UK (CRUK). The study includes organoids derived from colorectal, oesophageal, ovarian, pancreatic, and stomach cancer samples.

  Dataset EGAD00001015469

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__clear_cell_renal_cell_carcinoma

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001002608

• Caregiving as a Natural Stressor in Studies of the Role of Genes That Affect Serotonin Function in Regulating Risk Factors for Coronary Heart Disease (CAREGIVER)

  The burden of caregiving for an ill relative has been shown to interact with existing comorbidities to increase risk of several health outcomes including metabolic syndrome and blood pressure reactivity. The CAREGIVER study was developed to compare cardiometabolic risk factors in caregivers and controls. These risk factors include physiologic measures, psychologic measures, neighborhood characteristics, and genetic and genomic factors. DNA and plasma were collected and used for examination of cardiometabolic and stress biomarkers, genotyping and methylation analysis.

  Study phs001747

• Characterization of a New Case of XMLV (Bxv1) Contamination in the Human Cell Line Hep2 (Clone 2B) Using High-Throughput DNA- and RNA-Seq

  We have sequenced DNA and RNA from the Hep2 (clone 2B) cell line (Sigma-Aldrich catalog number: 85011412-1VL) using short read Illumina sequencing. We show that this cell line is indistinguishable from the HeLa cell line (as mentioned on the Sigma-Aldrich website) by mapping integrations of the human papillomavirus 18. We also show that the cell line is contaminated by the Bxv1 xenotropic murine leukemia virus. This contamination has to be taken into account when using the cell line in future experiments.

  Study phs001944

• Impact of Mutated CTCF DNA binding sites of Topologically associating domains on nearby Cancer Gene Regulation: A Multi-Omics Analysis

  Cutaneous squamous cell carcinoma (cSCC) is the most common lethal malignancy world-wide. Due in most part to the extremely high mutational burden (TMB) in cSCC, making sense of it’s non-coding and regulatory regional genomic variation has lagged that of other far less common cancers. This study presents the first investigation of mutations at CCCTC-binding factor binding sites (CTCFbs) of Topologically associating domains (TAD) across defined cSCC progression stages—primary non-metastatic (PNM), primary metastat-ic (PM), and lymph node metastasis (LNM).

  Study EGAS50000001686

• Identification of fusion transcripts by RNA-sequencing and Whole genome sequencing of a METABRIC patient sample

  Fusion transcripts and their exact breakpoints were identified in RNA-seq data (30X) of an ER-,HER2+ breast cancer. DNA-level breakpoints associated with the fusion events were determined by analyzing whole genome sequencing (WGS) data (30X) from the same donor. The RNA-seq and WGS data for this case were generated on the Illumina platform using standard protocols. The patient (MB-0152) derives from the METABRIC cohort for which array based copy number and gene expression data were previously described (EGAS00000000083).

  Study EGAS00001002475

• RUNX1 mutated families show phenotype heterogeneity and a somatic mutation profile unique to germline predisposed AML

  We present the clinical phenotypes and genetic mutations detected in 10 novel RUNX1 mutated FPD-MM families. Genomic analyses on these families detected two partial gene deletions, three novel mutations and five recurrent mutations as the germline RUNX1 alterations leading to FPD-MM. On 15 individuals, across the 10 families, we performed additional whole exome or myeloid panel sequencing on blood or bone marrow to determine somatic mutations that co-exist with the germline RUNX1 mutation in tumour and pre-leukaemic states.

  Study EGAS00001004273

• 16S rRNA gene V4 region sequencing data, ASV profiles, and sample metadata of human faecal samples predominantly from the Estonian population

  This dataset comprises 16S rRNA gene V4 region amplicon sequencing data generated from 1,826 human faecal samples, predominantly from the Estonian population. The dataset includes raw sequencing reads and processed amplicon sequence variant (ASV) outputs, consisting of ASV abundance tables, representative ASV sequences, and taxonomic assignments. In addition, a sample metadata table is provided, containing sample and host information, including sample identifier, sequencing run identifier, date of sampling, sex, age, height, weight, nationality, disease status, and Bristol stool type. Sequencing was performed using the Illumina MiSeq and iSeq 100 platforms. The cohort includes individuals with no reported disease (n = 889), gastrointestinal diseases (n = 217), allergies and asthma (n = 194), thyroid gland disorders (n = 117), cardiovascular diseases (n = 103), various general health conditions (n = 139), cancer (n = 28), diabetes (n = 20), gynaecological issues (n = 7). Disease status was unavailable for 112 samples.

  Dataset EGAD50000002306