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• Whole exome data from PMID27216186

  This dataset comprises complete exome data from from the study PMID27216186 (Harbst & Lauss et al, Cancer Research 2016). These data are from 49 samples (tumor and matched normal) from 8 patients representing multi-region sequencing of human melanoma. Files are in the BAM format and contain aligned and processed data used for e.g. somatic variant calling. The sequencing libraries were constructed using SureSelect target enrichment with Clinical Research Exome Panel (Agilent) and sequenced on a HiSeq2500 (Illumina).

  Dataset EGAD00001008149

• Single-cell RNA and TCR sequencing of BALF from 11 ICI-pneumonitis patients and 6 controls

  Dataset containing the FASTQ files of RNA (scr*) and TCR (vdj*) sequencing of 17 bronchoalveolar lavage fluid samples collected from ICI pneumonitis (n=11) and control (n=6) patients. To comply with GDPR regulations, please note that individual sample identifiers used for this data deposit (alphabetical ID) are different from and cannot be traced back to the patient identifiers used throughout the manuscript (numerical ID).

  Dataset EGAD00001009723

• Psoriasis Patient PBMC scRNA-seq data

  This dataset contains raw and processed data of four scRNA-seq PBMC samples from four Psoriasis patients (Pso3 = male, Pso4 = female, Pso7 = female, Pso8 = male). Raw sample libraries were prepared with 10x 5'-kit v2 multiplexing the individual samples using TrueSeq barcoded antibodies to stain the cells. Resulting sequencing data consists of four FASTQs (2 x antibody multiplex to demultiplex the samples + 2 x transcriptome data containing the typical cell x UMI barcode data for count matrix generation). The raw sequencing data was processed with cellranger 6.0.1 with the GRCh38 3.0.0 reference and cell to sample assignment was subsequently done with couhto 1.1.0 (https://github.com/dmalzl/counhto) employing the same algorithm as cellranger multi (couldn't be used here though as multi does not handle 5'-chemistry data). Processed data contains all main outputs of cellranger count in raw text format or in h5 formats including the used feature reference for (i.e. antibody barcode to sample assignment) as well as the computed cell to sample assignment computed by counhto. For further details including all used code in the analysis of the data please consult https://doi.org/10.5281/zenodo.13846873

  Dataset EGAD50000001102

• Targeted_replication_of_LVOTO_genes

  Non-syndromic cases of congenital heart defects (CHD) exhibit variable modes of inheritance (Mendelian and non-Mendelian). Several studies have identified strong candidates in humans by taking a candidate gene approach as well as by using whole exome next generation sequencing (NGS). So far these studies could only explain a minor fraction of the observed phenotype in humans, most of them in syndromic cases and no single study has focused on the subset of cases with left ventricular outflow tract obstruction (LVOTO). To discover novel disease-causing genes a large cohort of patients with LVOTO, approximately 100 cases, 25 families and 100 trios have been exome sequenced. This study based on NGS sequencing data yielded several known and novel compelling candidate genes, such as MYH6, NR2F2 and MYH11, but also novel ones, such as ITGB4. To evaluate the significance of our findings in a replication cohort we assembled another 1614 cases with an LVOTO phenotype from our collaborators in Toronto, Berlin and Amsterdam. Targeted resequencing in this additional cohort will help to find additional cases with mutations in the identified candidate genes to strengthen genotype-phenotype association. We will use control data from the INTERVAL project for case/control analyses The pulldowns will be performed as 24-plex ISC with 192 or greater indexes, and the sequencing will be performed with 192 samples per lane, requiring 9 lanes of sequencing.

  Study EGAS00001001238

• Use of Deep Sequencing to Dectect Clonal Mutations In Sun Exposed Skin Epidermis

  This study aims to define the landscape of somatic mutations in sun exposed human skin by deep sequencing, analyse their frequency and use the data to infer the effect of mutations on proliferating cell behaviour. The frequency of each mutation will reflect the size of the clone of cells in the tissue sample. By analyzing small samples, clones with as few as 100 cells will be detectable. Allele frequency distributions for each mutation will be used to infer cell fate using published methods (Klein et al. 2010). This study will shed unprecedented light on the early clonal events that lead to the emergence of cancer.

  Dataset EGAD00001001090

• Dataset for Multiple Myeloma WGS data, part 2

  This dataset contains 518 case and control WGS sequencing samples of patients with multiple myeloma. Sequencing was performed on Illumina NovaSeq 6000 and HiSeq X using TruSeq Nano DNA Kits. The sequencing was always paired.

  Dataset EGAD50000000681

• Dataset for Multiple Myeloma WGS samples

  This dataset contains 221 case and control WGS sequencing samples of patients with multiple myeloma. Sequencing was performed on Illumina NovaSeq 6000 and HiSeq X using TruSeq Nano DNA Kits. The sequencing was always paired.

  Dataset EGAD50000000682

• Dataset for acute myeloid leukemia samples

  This dataset contains RNA, ATAC and WGS sequencing data of 9 acute myeloid leukemia samples. Sequencing was performed on Illumina HiSeq 2000, HiSeq 4000, NovaSeq 6000 and HiSeq X Ten. The sequencing was always paired.

  Dataset EGAD50000000175

• Low-coverage Whole Genome Sequencing, Colorectal advanced adenomas, NKI-AvL TGO COCOS series

  For this tissue dataset, we applied low-pass whole genome sequencing to 96 advanced adenomas. Advanced adenomas were classified as lesions with low-risk or high-risk of progression, according to the presence of specific DNA copy number changes (Carvalho et al, CancerPrevRes, 2018).

  Dataset EGAD00001004078

• MCO colorectal cancer genomics at UNSW

  This dataset contains DNA sequencing data from 95 colorectal cancer and matched-normal samples. The dataset contains targeted deep sequencing of selected regulatory elements in 95 cancer and matched-normal samples, and data for one sample that was additionally whole-genome sequenced (cancer and matched-normal).

  Dataset EGAD00001004582

• NIHR-BioResource Rare Diseases - Neurodevelopmental disorders

  This dataset contains short-read whole-genome sequencing data for individuals with neurodevelopmental disorders and their relatives from the NIHR-BioResource Rare Disease Consortium.

  Dataset EGAD00001004456

• Gene regulation of human CD4+ Treg ChM-seq

  This dataset maps gene expression regulation in human primary regulatory CD4+ T cells (Tregs). It includes whole genome sequence data for ChM-seq (118 H3K4me3, 118 H3K27ac and 6 inputs). The final quality filtered set included 91 individuals with H3K27ac ChM-seq and 88 with H3K4me3 ChM-seq.

  Dataset EGAD00001004828

• Panel sequencing data for Molecular Characterization of ETMRs

  This dataset contains panel sequencing data from 33 samples. Targeted sequencing was performed by creating libraries using the Agilent SureSelect XT technology. Libraries were sequenced using molecular barcode-indexed ligation-based sequencing using a NextSeq500 (Illumina) instrument. Between three and six lanes per sample have been sequenced resulting in 262 Fastq files (paired end).

  Dataset EGAD00001006208

• 41 CRC Exome bam + 4 CRC paired fastq from EGAS00001002477 study

  This dataset contain 45 pairs of colorectal tumor and adjacent normal tissue. Four of them are from a previous study EGAS00001002477. For each sample a BAM was generated by aligning to GRCh37. Those colorectal cancer all have the MSI phenotype.

  Dataset EGAD00001006666

• ChIP-sequencing in human monocyte differentiation

  This dataset consists of ChIP-seq data from human monocytes, monocyte-derived dendritic cells as well as monocyte-derived cells that were subjected to siRNA treatment targeting CTCF or RAD21. ChIP-sequencing was done for H3K27, RAD21 and CTCF. In total, the data set includes 120 samples.

  Dataset EGAD00001007954

• HipSci whole exome sequencing for embryonic stem cell control lines

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we use commercially available embryonic stem cell lines as control samples against which to compare HipSci's iPS cell lines. We performed whole exome sequencing using Agilent whole exome pulldown method.

  Study EGAS00001001726

• MM samples for epigenomic translocation of H3K4me3 broad domains following super-enhancer hijacking

  Chromosomal translocations are important drivers of haematological malignancies whereby proto-oncogenes are activated by juxtaposition with super-enhancers, often called enhancer hijacking. To examine this phenomenon we used ChipSeq based on a combination of six histone modifications as follows: H3K4me1, H3K4me3, H3K9me3, H3K27me3, H3K27Ac and H3K36me3. Samples are patient-derived xenografts generated by passaging primary patient CD138+ selected cells through the SCID-rab myeloma mouse model.

  Study EGAS00001005684

• International Collaboration of Incident HIV and HCV in Injecting Cohorts (InC3)

  This study represents a merged international multi-cohort project of pooled biological and behavioral data from ten prospective cohorts of injection drug users (Grebely J, Morris MD, Rice TM, Bruneau J, Cox AL, Kim AY, et al., 2012, PMID: 23203695). Of the 10 cohorts, six provided data and samples for the genome wide association study (GWAS) entitled “Genetic Analysis of Opioid Addiction in People Who Inject Drugs”. The InC3 cohorts included in the GWAS were: i) Australian Trial in Acute Hepatitis C (ATAHC-I, Sydney); ii) Hepatitis C Incidence and Transmission Study in Prison (HITS-p) (Sydney); iii) Hepatitis C Incidence and Transmission Study in Community (HITS-c) (Sydney); iv) HepCo Study (Montreal); v) SuperMIX Study (combining the Networks II & MIX studies, Melbourne); and vi) the UFO Study (San Francisco).

  Study phs002310

• This study aims to evaluate the relationship between cardiometabolic risk factors and the most common genetic variation (SNPs)

  Comprehensive data on lifestyle-related modifiable factors, sociodemographic, anthropometric, economic, biochemical, and genetic markers related to the occurrence of cardiometabolic diseases as part of the observational cross-sectional survey “2015 Health Survey of Sao Paulo with Focus on Nutrition (2015 ISA-Nutrition)”, a population-based study. Data of 805218 SNPs for 841 individuals was genotyped using the Axiom™ 2.0 Precision Medicine Research Array in the Thermo Fisher Scientific laboratory (Affymetrix Inc, Santa Clara, CA).

  Study EGAS00001007818

• Tools

  EGA Tools This page provides details of the applications available at the EGA. Submission Tool Description EgaCryptor Encrypt and create md5sum values. Crypt4gh Encrypt, decrypt or re-encrypt files. INBOX Upload your files once encrypted. FTP Upload your files once encrypted. Submitter Portal Submit and manage your submission metadata online (SEQUENCING AND PHENOTYPE ONLY) Submitter Portal API Submit and manage your submission metadata programmatically. Webin Submit and manage your submission metadata online (array data) Webin API Submit metadata using XML files. Aimed to array-based submissions. Star2xml Format conversion tool to transform tabular formats (e.g. spreadsheets) into EGA's XMLs. Used for large programmatic submissions. Data Access Tool Description DAC Portal Manage and control data access request. Download Tool Description PyEGA3 Download and decrypt datasets requested through your EGA web account. Live Outbox Download and decrypt datasets requested through your EGA web account. Fuse Client A quick and convenient way to browse through EGA files without the need for complete downloads. EGA QuickView A quick and convenient way to browse through EGA files without the need for complete downloads.

  Documentation tools

• Systemic mutagen exposures reported by normal kidney cell genomes - peripheral blood samples (NanoSeq)

  Lifestyle, environmental and other exposures to exogenous mutagens generate somatic mutations in normal human cells in vivo and increase cancer risk. However, the global repertoire of exogenous mutagen exposures is uncertain. Using single-molecule duplex sequencing of normal kidney (n=319) and blood (n=272) samples from 10 countries, we show that kidney proximal tubule cells exhibit higher mutation rates than most normal cell types despite low cell division rates. Compared to cells from kidney glomeruli, medulla, distal tubules, or peripheral blood, proximal tubule cells show marked enrichment of mutational signatures due to the exogenous carcinogenic mutagens, aristolochic acids, and of several signatures of unknown causes. The results suggest the existence of multiple, common, systemically circulated mutagens affecting human populations and indicate that the genomes of kidney proximal tubule cells report such exposures with high sensitivity.

  Dataset EGAD00001015824

• Systemic mutagen exposures reported by normal kidney cell genomes - microdissected kidney samples (NanoSeq)

  Lifestyle, environmental and other exposures to exogenous mutagens generate somatic mutations in normal human cells in vivo and increase cancer risk. However, the global repertoire of exogenous mutagen exposures is uncertain. Using single-molecule duplex sequencing of normal kidney (n=319) and blood (n=272) samples from 10 countries, we show that kidney proximal tubule cells exhibit higher mutation rates than most normal cell types despite low cell division rates. Compared to cells from kidney glomeruli, medulla, distal tubules, or peripheral blood, proximal tubule cells show marked enrichment of mutational signatures due to the exogenous carcinogenic mutagens, aristolochic acids, and of several signatures of unknown causes. The results suggest the existence of multiple, common, systemically circulated mutagens affecting human populations and indicate that the genomes of kidney proximal tubule cells report such exposures with high sensitivity.

  Dataset EGAD00001015827

• Transcriptomics of Liver and PBMCs in Alcohol-Associated Liver Disease

  This study was designed to characterize the transcriptome of alcohol-associated hepatitis using RNA sequencing (RNA-seq) technology for both liver tissue biopsies and peripheral blood mononuclear cells (PBMCs) extracted from blood samples, in order to identify expressed genes that are markers of the disease. To distinguish genes that differentiate alcohol-associated hepatitis from other inflammatory liver diseases, we compared the RNA-seq data generated from participants with alcohol-associated hepatitis, alcohol-associated cirrhosis, chronic hepatitis C infection, non-alcohol-associated fatty liver disease, and healthy controls. We utilized computational approaches to demonstrate that gene expression data generated from either liver tissue or blood samples can be used to identify a small set of gene biomarkers to distinguish between these liver diseases. The raw RNA-seq data will be available through dbGaP.

  Study phs003112

• Somatic mutations and single cell transcriptomes reveal the root of malignant rhabdoid tumours

  Like many childhood cancers, malignant rhabdoid tumours (MRT) are thought to arise from aberrant foetal development. Although MRT predominantly exhibit a mesenchymal phenotype, it has been suggested that the foetal root of MRT lies in neural crest development. Here, we combine phylogenetic analyses of MRT, single cell mRNA assays, and functional experiments in patient-derived MRT organoids, to define the embryological origin of MRT and explore therapeutic avenues that may drive MRT differentiation. Phylogenetic analyses from the distribution of somatic mutations revealed that MRT were related to neural crest-derived, but not to mesodermal tissues, providing direct evidence of the neural crest origin of MRT in humans. In MRT organoids, reversal of the principal driver event underpinning MRT, SMARCB1 loss, induced differentiation along mesenchymal pathways. Together, these findings placed MRT cells on a developmental trajectory of neural crest to mesenchyme conversion, and defined the transcriptional changes underpinning MRT differentiation. Searching perturbation databases for agents that mimic these mRNA changes, we identified HDAC and mTOR inhibition as potential differentiation agents. Treatment of MRT organoids with this drug combination induced proliferation arrest with transcriptional changes akin to SMARCB1 re-expression. Our study defines the embryological root of MRT and proposes a differentiation treatment for this often fatal childhood cancer.

  Dataset EGAD00001006296

• Dataset belonging to the article "Genotyping from targeted NGS data based on a small set of SNPs correctly matches patient samples"

  This dataset consists of raw sequencing data from targeted next generation sequencing of samples from patients with chronic lymphocytic leukaemia. These samples were used to validate an approach for detection of sample mislabelling and swapping in clinical cohorts using single nucleotide polymorphisms (SNPs), as described in the associated article. The data are divided into two parts - data from the initial validation experiment (discovery cohort) and data from an additional independent cohort.

  Dataset EGAD50000000757