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• Whole exome sequencing data for Molecular Characterization of ETMRs

  This dataset contains exome sequencing data from 21 samples. Sequencing of samples using whole-exome sequencing was per- formed by creating libraries using the IlluminaTruSeq exome enrich- ment kit following the manufacturer’s instructions after size selection. Size selection was performed by fractionation using a Covaris ultra- sonicator and subsequent selection was performed using a 1.5% gel Pippin Prep cassette (Sage Science). One lane per sample has been sequenced resulting in 42 Fastq files (paired end).

  Dataset EGAD00001006210

• RRBS profiling for a cohort including 88 precancer specimens from 62 resected lung nodules from 39 patients including atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (ADC) and 39 matched normal lung tissues.

  To study the evolution of DNA methylation at genome level and methylation intra-tumor heterogeneity (ITH) during early lung carcinogenesis, we performed multiregional reduced representation bisulfite sequencing (RRBS) of 127 resected lung samples from 39 patients using single end library Hiseq3000.

  Dataset EGAD00001006367

• The Xq22.3 contiguous gene deletion syndrome (ATS-ID): from genotype to further delineation of the phenotype

  Approximately 200 ng of high-quality of genomic DNA samples were used for library preparation. DNA libraries were prepared using the Human Core Exome Kit according to manufacturer’s recommendations (Twist Bioscience, San Francisco, CA, USA) and then sequenced on Illumina NovaSeq 6000 (Illumina, Inc., san Diego, CA, USA). Detailed protocol of WES data processing and variant analysis are available in Supplementary data.

  Dataset EGAD00001007740

• Drug-induced epigenomic plasticity reprograms circadian rhythm regulation to drive prostate cancer towards androgen-independence

  ChIP-seq for AR, FOXA1 and H3K27ac in primary prostate tumors before and after 3 months of neoadjuvant enzalutamide treatment. RNA-seq expression data of primary prostate tumors before and after 3 months of neoadjuvant enzalutamide treatment.

  Dataset EGAD00001008562

• 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

• Multi-region sequencing of 10 neuroblastoma cases

  To investigate intratumour heterogeneity and to better understand tumour evolution in neuroblastoma, we have performed a multi-region whole-exome sequencing on a total of 51 spatially separated tumor samples from 9 primary neuroblastomas (2 low-risk, 1 intermediate-risk and 6 high-risk) and 1 relapsed neuroblastoma. We also assessed the impact of chemotherapy on the clonal expansion by sequencing tumour regions from one medium risk and one high-risk tumour for which we had matched samples obtained at diagnosis and after chemotherapy.

  Dataset EGAD00001008020

• WGS data from LCNEC patient derived tumor organoids (PDTOs) and matched parental tumors - SA

  The dataset includes cram files from WGS of 2 LCNEC tumors and matched PDTOs. For all tumors, cram files from WGS of matched normal tissue derived organoids from the corresponding patients is included. Analysis VCF files are also included in the dataset. The sequencing was done with a NovaSeq 6000 instrument.

  Dataset EGAD00001009990

• Bulk RNA-Seq

  Human data for transcriptome (bulk RNA-Seq) in eight B-cell precursors: HSC, CLP, pro-B, pre-B, Immature B, Transitional B, Naive B CD5-, Naive B CD5+ cells

  Dataset EGAD00001010906

• Bulk ATAC-Seq Illumina NextSeq 500 (10M reads)

  Human data for chromatin accessibility (ATAC-Seq) in eight B-cell precursors: HSC, CLP, pro-B, pre-B, Immature B, Transitional B, Naive B CD5-, Naive B CD5+ cells

  Dataset EGAD00001010908

• scRNA-seq

  This dataset gather scRNAseq data performed for MM.1S cell line in control and dex conditions at 4h and 24h

  Dataset EGAD00001011139

• Sequencing data for oesophageal and related samples - Linossi et al

  Data supporting: "Utility of ctDNA assessment after six weeks of immunotherapy to predict radiological response in advanced oesophageal cancer" Linossi et al

  Dataset EGAD00001015434

• RNA-Seq dataset for Malignant rhabdoid study

  Study describing the dynamics of chromatin organization within malignant rhabdoid tumors. This study describes how this chromatin organization changes upon SMARCB1 rescue within patient-derived organoid models from malignant rhabdoid tumors. Identification of a novel super-enhancer of MYC and identification of patient-specific enhancer utilization to activate MYC expression in these tumors.

  Dataset EGAD00001011819

• CUT&RUN/ChIP-Seq dataset for Malignant rhabdoid study

  Study describing the dynamics of chromatin organization within malignant rhabdoid tumors. This study describes how this chromatin organization changes upon SMARCB1 rescue within patient-derived organoid models from malignant rhabdoid tumors. Identification of a novel super-enhancer of MYC and identification of patient-specific enhancer utilization to activate MYC expression in these tumors.

  Dataset EGAD00001011821

• TenK10K Phase 1: Whole Genome Sequencing Alignments

  Whole genome sequencing was performed for 1,925 samples from phase 1 of the TenK10K project. Sequencing was done with Illumina 2 x 150bp chemistry on a NovaSeq 6000 instrument to achieve mean 30x coverage. Sequence reads were aligned to the GRCh38 reference assembly with a fork of DRAGMAP v1.3.1. This dataset is comprised of 1,925 alignment files in cram format, and their corresponding index files.

  Dataset EGAD50000002466

• Genomic Profiling Reveals Spatial Intra-tumour Heterogeneity in Follicular Lymphoma

  Follicular lymphoma (FL) is an incurable indolent non-Hodgkin’s lymphoma (NHL) that behaves heterogeneously and is synonymous with the reciprocal translocation t(14;18)(q32;q21), leading to aberrant constitutive over-expression of BCL2 [ref]. High risk groups with poor overall survival include patients that transform to a high grade lymphoma, most commonly diffuse large B cell lymphoma (DLBCL) or progress early (within 2 years) of receiving treatment. Recently several studies have shed light on the diverse genomic landscape of FL, with frequently mutated genes including those involved in chromatin remodelling, (CREBBP, KMT2D, EZH2, EP300), immune modulation (TNFRSF14), JAK-STAT (STAT6, SOCS1), NF-ĸB (CARD11, MYD88, TNFAIP3) and mTORC1 signalling (RRAGC) [ref]. To date, the majority of these studies have either focussed on inter-patient genetic heterogeneity or established the extent of clonal heterogeneity as a patient’s tumour evolves over time. Furthermore, these temporal studies have alluded to the existence of a tumour-repopulating population (referred to as the common progenitor cell (CPC)) that evades treatment and acts as a reservoir, seeding each subsequent relapse and transformation event. Although these previous studies have illuminated the longitudinal clonal dynamics that occur in FL, our understanding of the degree of spatial or intra-tumour heterogeneity (ITH) that exists within an individual patient thus far remains limited. Earlier studies have predominantly focused on differences in cytological grade and immunophenotype between spatially separated lymph nodes and bone marrow, the most common site of extra-nodal involvement in FL, with genomic profiling restricted to examining somatic hypermutation patterns in IgVH genes [ref]. In contrast next generation sequencing has been increasingly utilised in solid organ malignancies to derive comprehensive genomic profiles from spatially separated sites. The seminal study by Gerlinger et al revealed profound differences in the genetic make-up between individual primary and metastatic sites of renal cell carcinoma [ref]. Significant heterogeneity has since been demonstrated both between and within lesions in the same patient in lung, pancreas and breast cancer with presumed driver mutations distributed within the “branches” of the evolutionary phylogenetic tree, suggesting that a single biopsy is incapable of capturing the full genomic heterogeneity of an individual’s malignancy [ref]. This geographical heterogeneity not only adds to the diverse pool of tumour subclones that may contribute to drug resistance mechanisms but importantly, presents a major obstacle for precision-based approaches focussed on targeting specific lesions within a single biopsy. In FL, the exponential increase in clinical trials using novel agents such as EZH2, PI3K and BTK inhibitors reflects this shift in cancer care and along with the development of molecular prognostic scores such as the m7-FLIPI highlights the clinical need to accurately define genomic alterations with clinical relevance. As the majority of FL patients manifest disseminated tumour involvement, we sought to uncover the extent and clinical importance of spatial heterogeneity in FL by comprehensively genetically profiling 22 synchronously removed spatially separated biopsies from 9 patients. Using a combination of whole exome and targeted deep sequencing, our results inferred the complex subclonal architecture within these tumours and the mutational differences between anatomical sites, demonstrating cases with significant intrinsic genetic diversity.

  Study EGAS00001002492

• Collaborative Study of Genes, Nutrients and Metabolites (CSGNM)

  While many genetic and metabolic studies focus on understanding disease states, this genome wide association study (GWAS) was designed to understand the influence of genetic variants on circulating metabolites and factors in normal, healthy individuals. Over 2500 healthy, ethnically Irish college students attending Trinity College Dublin completed a health and diet questionnaire and provided a non-fasting blood sample to be used for genetic and metabolic analysis. The questionnaire was designed to collect information on age, sex, height, weight, medical conditions, smoking, dietary habits, and consumption of alcohol, fortified foods, and supplements. Extracted DNA was genotyped using the Illumina HumanOmni1-Quad Beadchip. Metabolites were measured using a number of methods and focused on those relevant to the folate/vitamin B12 pathway.

  Study phs000789

• Multimodal Profiling of 500,000 Memory T Cells from a Tuberculosis Cohort Identifies Cell State Associations with Demographics, Environment, and Disease

  We conducted CITE-seq to measure whole transcriptome gene expression and surface expression of 31 proteins. We assayed >500K memory T cells from 259 donors from a tuberculosis progression cohort (128 cases: former progressors and 131 controls: non-progresssors/latent infection) >4 years post-infection after returning to immune steady state. We defined 31 memory T cell states influenced by age, sex, genetic ancestry, and season. After correcting for these covariates, we found that one cell state (C-12), resembling the T helper cells Th17s, were depleted in cases compared to controls. When sorted ex vivo, this state responds to polyclonal or Mycobacterium tuberculosis (Mtb) peptide antigen stimulation with interleukin-17 (IL-17) or interferon gamma (IFNg).

  Study phs002467

• Cross-site Concordance Evaluation of Tumor DNA and RNA Sequencing Platforms of CIMAC-CIDC Network

  The Cancer Immune Monitoring and Analysis Centers (CIMACs) and the Cancer Immunologic Data Commons (CIDC)  has engaged in efforts to harmonize Whole-exome (WES) and RNA-sequencing (RNA-seq) data from three different experimental platforms (MD Anderson, NCI MoCha lab, and Broad Institute) and are using a series of developed pipelines to process the early trial samples. To evaluate the consistency of tumor WES and RNA-seq profiling platforms across different centers, the CIMACs-CIDC conducted a systematic harmonization study. DNA and RNA were centrally extracted from fresh frozen (FF) and formalin-fixed paraffin-embedded (FFPE) non-small cell lung carcinoma (NSCLC) tumors and distributed to three centers for WES and RNA-seq profiling

  Study phs002295

• The PRIME-AIR Study: Positive End-Expiratory Pressure, Recruitment, Incentive Spirometry, Muscle Relaxant Optimization, Preoperative Education, Postoperative Early Ambulation, Individualized, and Reinforced

  Data Access NOTE: Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions.The PRIME-AIR study ("Positive end-expiratory pressure, Recruitment, Incentive spirometry, Muscle relaxant optimization, preoperative Education, postoperative early Ambulation, Individualized, and Reinforced") was a prospective multi-center randomized controlled pragmatic trial, with a blinded assessor, to compare post-operative pulmonary complications (PPCs) in patients with an individualized anesthetic-centered intervention (including individualized mechanical ventilation positive end-expiratory pressure (PEEP) management to maximize respiratory system compliance and minimize driving pressures, a neuromuscular agent and subsequent reversal, and post-operative lung expansion and early mobilization) versus usual care.

  Study phs003926

• Genomic subtypes and cellular phenotypes of high-grade endometrial carcinoma

  Based on the mechanism of carcinogenesis, endometrial cancer (EC) is classified into two major types, Type I and Type II. Type I EC is characterized by G1/G2 histology, accounting for about 80% of all uterine carcinomas. On the other hand, Type II EC, which often develops after menopause, is estrogen-independent and consists of serous and clear cell carcinomas. G3 EC is often classified as a Type II EC, but the pathogenesis is thought to be a mixture of estrogen-dependent and estrogen-independent carcinogenesis. We will conduct an integrative genomic analysis to clarify the pathogenesis of Type II EC and redefine its classification by combining genomic status with cell phenotypes reflected in gene expression profiles.

  Study JGAS000753

• The acute effects of morning bright light on the human white adipose tissue transcriptome: exploratory post hoc analysis

  The circadian rhythm of the central brain clock in the suprachiasmatic nucleus (SCN) is synchronized by light. White adipose tissue (WAT) is one of the metabolic endocrine organs containing a molecular clock, and it is synchronized by the SCN; excess WAT is a risk factor for health issues including type 2 diabetes mellitus (DM2). We hypothesized that bright-light exposure would affect the human WAT transcriptome. Therefore, we analyzed WAT biopsies from two previously performed randomized cross-over trials (trial 1: lean healthy men, and trial 2: men with obesity and DM2). RNA sequencing results showed major group differences between men with obesity and DM2 and lean healthy men, as well as a differential effect of bright light exposure.

  Study EGAS50000001206

• Transcriptome analysis of human longitudinal whole blood samples from PCR-positive and PCR-negative adults following controlled inoculation with Influenza A (H3N2) virus.

  Transcriptome analysis of influenza A (H3N2) human challenge samples. Understanding of the transcriptomic profile of individuals in early influenza infection is limited. To investigate this, longitudinal whole-blood samples (n=178) were taken from adult participants following controlled inoculation with Influenza A H3N2 virus (sampling at baseline (0) and days 1, 2, 3, 7, 10 and 14 post-challenge). Most participants became influenza PCR-positive; a minority remained PCR-negative. Total RNA was extracted from PAXgene tubes before undergoing globin and rRNA depletion. DNA libraries were constructed using the NEBNext® Ultra™ II Directional RNA Library Prep Kit for Illumina. All samples were then sequenced using Illumina NovaSeq 6000.

  Study EGAS50000000679

• Integrated genomic analysis identifies recurrent mutations and evolution patterns driving the initiation and progression of follicular lymphoma.

  follicular lymphoma (FL), the most common indolent non-Hodgkin’s lymphoma, remains incurable. A well-recognized complication of FL is its transformation to a diffuse large B-cell lymphoma (DLBCL)-morphology in a subset of patients, for which the clinical outcomes are poor. Recent genetic profiling and single case studies of donor-derived FL following stem cell transplantation had alluded to the putative existence of a ‘long lived’ tumor-initiating progenitor cell compartment from which successive disease events occurred. To chronicle the genetic changes associated with progression to transformation, we conducted whole-genome sequencing (WGS) of FL-tFL pairs and matched germline (GL) samples from six patients, a total of 20 genomes.

  Study EGAS00001000399

• RNA-seq study of longitudinal blood cell samples from children at risk of type 1 diabetes

  The appearance of type 1 diabetes (T1D)-associated autoantibodies is the first and only measurable parameter to predict progression toward T1D in genetically susceptible individuals. However, autoantibodies indicate an active autoimmune reaction, wherein the immune tolerance is already broken. Therefore, there is a clear and urgent need for new biomarkers that predict the onset of the autoimmune reaction preceding auto-antibody positivity or reflect progressive b-cell destruction. Here we report the mRNA sequencing–based analysis of 306 samples including fractionated samples of CD4+ and CD8+ T cells as well as CD4, CD8 cell fractions and unfractionated PBMC samples longitudinally collected from seven children who developed beta-cell autoimmunity (Case subjects) at a young age and matched control subjects.

  Study EGAS00001004071

• Test dataset: Sequence and variant data from public 1000 Genomes Project

  This is a test dataset derived from public data of the 1000 Genomes Project. Its purpose is not to allow for any inference about cohort data or results, but to aid bioinformaticians in the technical development and testing of tools, as well as data consumers in learning how to access information. This dataset consists of 2508 samples from the 1000 Genomes Project (https://www.nature.com/articles/nature15393). Samples' (e.g. NA18534) data can be accessed through the IGSR portal (e.g. https://www.internationalgenome.org/data-portal/sample/NA18534) or their corresponding folder at the 1000 Genomes' FTP site (e.g. http://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data_collections/1000_genomes_project/data/CHB/NA18534/exome_alignment/). There are several different types of data this dataset encompasses: Variant Calling Format (VCF, or its binary counterparts BCF) files, both joint (e.g. ALL_chr22_20130502_2504Individuals.vcf.gz) and split (HG01775.chrY.vcf.gz); exome sequencing CRAM files (e.g. NA18534.GRCh38DH.exome.cram); whole genome sequencing CRAM/BAM files (e.g. NA19239.cram). Additionally, there are multiple files that were sliced to create shorter files, which allows for a quick download, formated as "{FILE-INFO}__{NUMBER-OF-READS}r__{CHR}.{START-COORDINATE}-{END-COORDINATE}.{FILETYPE}" (e.g. "HG01500.GRCh38DH__90r__3.10000-10500__4.10000-10500.cram"). These files can be downloaded directly through the EGA-download-client PyEGA3 (https://github.com/EGA-archive/ega-download-client).

  Dataset EGAD00001003338