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• Identification of drug resistance genes in melanoma

  Our aim is to analyze the genome of human melanoma cell lines and short term culture from human melanoma samples in order to identify genes that confer drug resistance to clinically relevant targeted therapies. We will perform whole-exome sequencing, copy number variation analysis and methylome analysis in a collection of human melanoma cell lines and short term culture that will be then screened for drug sensitivity/resistance through a library of clinically relevant drugs and drug combinations. By the combined analysis of the genomic lesion and the drug sensitivity/resistance profile of different cell lines, we will look for genes whose mutation is associated to the sensitivity or resistance to a specific drug in different samples.

  Dataset EGAD00001001124

• Genetic background for the major psychiatric disorders in the general Finnish population

  Low coverage (4-6x) sequencing on samples from population cohorts (Finrisk, Health2000) will be done at Wellcome Trust Sanger Institute (WTSI) using Illumina HiSeq sequencing technology. We will produce 100bp paired end reads. Variants will be called using the 1000 Genomes Project pipeline. The samples have been selected from a national representative set of 8028 samples from persons of 30 years or older, which were screened for psychotic and bipolar disorders using the Composite International Diagnostic Interview, self-reported diagnoses, medical examination, and national registers.

  Dataset EGAD00001001250

• SCLC study George et al. - WGS data set

  Whole genome sequencing was performed with DNA extracted from fresh-frozen tumor and normal material. Short insert DNA libraries were prepared with the TruSeq DNA PCRfree sample preparation kit (Illumina) for paired-end sequencing at a minimum read length of 2x100bp. Human DNA libraries were sequenced to an average coverage of minimum 30x for both tumor and matched normal. Murine DNA libraries of tumor and matched normal were both sequenced to a coverage of 25x.

  Dataset EGAD00001001273

• Tam-Seq of HGSOC samples for fixative comparison study

  Targeted amplicon sequencing of samples as part of the study "Methanol-based fixation is superior to buffered formalin for next-generation sequencing of DNA from clinical cancer samples. The amplicon panel consists of 48 amplicons in TP53, PTEN, EGFR, PIK3CA, KRAS and BRAF genes as described previously [Forshew, STM 2012]. All libraries were pooled and quantify using DNA 1000 kit on Agilent 2100 Bioanalyzer and KAPA SYBR FAST ABI Prism qPCR Kit (KAPA Biosystems) on 7900HT Fast Real-Time PCR System (Applied Biosystems) according to the supplier's recommendations. Reads were aligned using bwa-mem v0.7.12-r1039 to the 1000 genomes version of human genome build GRCh37, retaining duplicate reads.

  Dataset EGAD00001001937

• COMPARE study: participants typed during UK Biobank version 2 array development phase

  The COMPARE study enrolled 29,066 British blood between donors between February 2016 and March 2017, the study aim is to find the optimum technology for haemoglobin screening (ISRCTN 90871183). All participants were at the time of recruitment active blood donors. The 4,796 participants in this dataset have consented to join the NIHR BioResource. Genotyping data was produced using the Thermo Fisher Scientific Axiom Genotyping platform. The UK Biobank version 2 array design was used, content on this array has been added to allow for accurate DNA based identification of human blood group antigens.

  Dataset EGAD00001005023

• Targeted_sequencing_of_blood_DNA_from_Human_twins (2019-05-31)

  The goals of this study is to investigate the prevalence and heritability of age-related clonal haemopoeisis (ARCH) in healthy elderly individuals.We will use a bespoke bait set to pull down DNA regions of interest in whole blood samples combined with HiSeq at a deep level . By correlating findings from each individual to their respective twin we hope to elucidate whether heritable traits influence the development of ARCH. a. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2019-05-31.

  Dataset EGAD00001005055

• Preeclampsia InterPregGen Consortium: Whole Genome Sequencing of 100 unrelated Kazakhs (DNA samples from the Scientific Center of Obstetrics, Gynecology and Perinatology, Almaty, Kazakhstan; Gulnara Svyatova, Principal Investigator

  Whole genome sequencing of 100 unrelated Kazakhs in order to impute genotypes into PE cases and controls from Kazakhstan and to provide genetic data and infrastructure for future genetic studies in Kazakhstan and Central Asia more generally and to fill a gap in worldwide information as Central Asia is not adequately represented in available genomic data. This dataset is one component of the InterPregGen FP7 project. DNA samples for this component were collected by InterPregGen Consortium collaborators at the Scientific Center of Obstetrics, Gynecology and Perinatology, Almaty, Kazakhstan (Gulnara Svyatova, Principal Investigator)

  Dataset EGAD00001005467

• Single cell RNA sequencing data in "Three-dimensional human alveolar stem cell culture models reveal infection response to SARS-CoV-2"

  This dataset includes a total of 5 single cell RNA sequencing (scRNAseq) data of SARS-CoV-2 infected human alveolar stem cell culture models. Two scRNAseq data were obtained from SARS-CoV-2 infection with MOI of 1.0 (1 for control and 1 for infected case) and the other three were obtained from SARS-CoV-2 infection with MOI of 0.1 in the study entitled "Three-dimensional human alveolar stem cell culture models reveal infection response to SARS-CoV-2". The 10x Chromium Single Cell 3' Reagent kits were used to generate libraries.

  Dataset EGAD00001006242

• TS and WGS data

  The dataset contains the targeted sequencing (TS) and the whole genome low pass (WGS) BAM files of the study. For the TS: Samples: TS_XXX There are normal and tumor DNA samples. Each DNA strand has been sequenced independently (PoolA and PoolB). A TruSeq Custom Amplicon panel of 20 genes frequently mutated in ILC and/or ER-positive BC in general was designed using DesignStudio from Illumina: AKT1, ARID1A, CDH1, ERBB2, ERBB3, ESR1, FOXA1, GATA3, IGF1R, JAK2, MAP2K4, MAP3K1, NF1, PIK3CA, PTEN, RB1, RUNX1, STAT3, TBX3, and, TP53. For the WGS: Samples: WGS_XXX There are normal and tumor DNA samples. Samples were sequenced to an average target coverage of 0.5X.

  Dataset EGAD00001006393

• Chracterising cellur pathways underlying CD3/CD28 activation of human CD4+ cells

  We devised an approach to disentangle the TCR and CD28 pathways upon stimulation in naive and memory primary human CD4+ T cells (Tcons) in response to defined stimulatory signals. Sorted Tcons were activated using a titration of anti-CD3 and anti-CD28 in combination as well as individually. As a control we cultured cells in the same conditions but without the stimuli. In total, we defined seven conditions from four individuals for sequencing. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/.

  Dataset EGAD00001006610

• Chracterising cellur pathways underlying CD3/CD28 activation of human CD4+ cells

  We devised an approach to disentangle the TCR and CD28 pathways upon stimulation in naive and memory primary human CD4+ T cells (Tcons) in response to defined stimulatory signals. Sorted Tcons were activated using a titration of anti-CD3 and anti-CD28 in combination as well as individually. As a control we cultured cells in the same conditions but without the stimuli. In total, we defined seven conditions from four individuals for sequencing. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ .

  Dataset EGAD00001006612

• H3Africa AWI-GEN Phase 1 Phenotype

  The phenotypic data for ~12500 samples of the AWI-Gen Phase 1 Population cross-sectional study of older adults (mostly between 40 and 60 years), men and women. Six study sites in four sub-Saharan African counties including Ghana, Burkina Faso, Kenya and South Africa. Some groups are missing data for specific variables. Data includes questionnaire data (demography, health history, family health history, behaviour and infection data); anthropometry; and laboratory assays on blood and urine.

  Dataset EGAD00001006425

• TENX069

  Transcriptome profiling by high-throughput sequencing for single cells for library TENX069 1 samples; filetype=fastq

  Dataset EGAD00001006483

• Oxford Nanopore targeted RNA-based amplicon data of 12 classical HLA genes

  The dataset consists of Oxford Nanopore targeted RNA-based amplicon data of 12 classical HLA genes (HLA-A, -B, -C, -DRA, -DRB1, -DRB3, -DRB4, -DRB5, -DQA1, -DQB1, -DPA1, and DPB1) of 50 healthy individuals. The 12 classical genes were sequenced in two separate gene pools on R9.4 flowcells using MinION sequencer. Per individual, gene pool 1 contains HLA-A, -B, -C, -DRB1, -DRB3, -DRB4, -DRB5, and -DPB1 and gene pool 2 HLA-DRA, -DQA1, -DQB1, and -DPA1. The dataset includes 100 fastq files of Oxford Nanopore 2D reads (50 for gene pool 1 and 50 for gene pool 2).

  Dataset EGAD00001006814

• Summary Statistics GWAS SSNS

  Column 1 “rsid”: SNP identifier Column 2 “chromosome”: name of chromosome on which the SNP is located Column 3: “position”: base pair position on the chromosome Column 4 “minor_test_allele”: the base that constitutes the minor allele Column 5 “major_allele”: the base that constitutes the major allele Column 6 “maf”: the frequency of the minor allele, indicated as a fraction of 1 Column 7 “allele_freq_cases”: the minor allele frequency in cases Column 8 “allele_freq_controls”: the minor allele frequency in controls Column 9 “regression_pvalue”: the p-value for the difference in allele frequency between cases and controls Column 10 “odds_ratio”: the odds ratio, as calculated using logistic regression under an additive model with adjustment for the first ten principal components of ancestry

  Dataset EGAD00001008782

• Whole exome and transcriptome sequencing of BPDCN

  This data set contains whole exome and transcriptome data from 47 case with BPDCN. For exome data, bam files are provided (mapped against GRCh38), for transcriptome raw fastq-files (paired-end data).

  Dataset EGAD00001008692

• Induction Failure in Childhood and Young Adult T-cell Acute Lymphoblastic Leukemia

  We carried out WGS and RNAseq on a cohort of 48 children and young adults with induction failure in T-cell Acute Lymphoblastic Leukemia (T-ALL) to identify genomic drivers of treatment resistance. The study includes WGS for 33 tumour/normal pairs and 15 tumour-only samples. In addition, there is RNAseq data for 37 cases.

  Dataset EGAD00001009058

• Single cell sequencing of human normal luminal cells

  The dataset includes 12 paired FASTQ files (6 samples) with single cell transcriptome sequencing data of normal breast luminal cells from ducts and TDLUs derived from reduction mammoplasties from three patients. Chromium Single Cell 3’ Reagent Kit v2 or v3 (10x Genomics) were used for processing of cells, whereafter sequencing was performed using the Illumina® NextSeq500/550 High Output Kit v2. Cell Ranger was used for generating FASTQ files and files from different lanes were concatenated prior to uploading the data to EGA. "R1" files include the feature barcodes and UMIs, while "R2" files include the reads.

  Dataset EGAD00001008499

• Single-cell omics data for COVID-19 patients

  Single-cell RNA-seq, single-cell ATAC-seq, and genotypes used in the analysis for the study "Altered and allele-specific open chromatin landscape reveal epigenetic and genetic regulators of innate immunity in COVID-19". The RNA-seq and ATAC-seq are raw data in FASTQ format while the genotypes are in the VCF format which was filtered and imputed (more details are available in the main text of the study).

  Dataset EGAD00001009331

• Immune Response Targeted Panel + B/TCR Profiling + AbSeq + Sample Tag Multiplexing

  Multiomics data for a cohort of 20 COVID-19 patients (10 patients mild, 3 patients moderate, 4 patients severe, 3 patients critical) obtained from peripheral blood mononuclear cells (PBMCs) from longitudinally sampled at hospital admission, discharge, and 1 month thereafter. The data has been obtained a multiwell-based single-cell technology (BD Rhapsody) that includes the targeted expression of BD Immune Response Targeted Panel, the TCR/BCR profiling and a set of 52 surface proteins. The samples of the different patients at different collection times were labelled using a cell hashing strategy with the BD Single-Cell Multiplexing Kit (6 samples for each run).

  Dataset EGAD00001011319

• Mechanisms of Extreme Genomic Instability at Large Transcribed Genes

  Inhibiting DNA replication leads to copy number variant (CNV) formation throughout the genome, especially at chromosome fragile sites (CFSs). We previously showed that these hotspots for genome instability reside in late-replicating domains associated with large transcribed genes. In this study, we compared aphidicolin (APH)-induced CNV and CFS frequency between wild-type cells and isogenic cells in which FHIT gene transcription was ablated. We further examined the impact of altering RNase H1 expression on CNV or CFS induction frequency and analyzed R-loop formation genome-wide in a human fibroblast cell line. Data sets include Bru-seq nascent RNA transcription, whole genome sequencing for replication timing, SNP microarray analysis, and DRIP-seq. Results suggest that large gene transcription is a determining factor in replication stress-induced genomic instability and that CFSs mainly result from transcription-dependent passage of unreplicated DNA into mitosis with low R-loop levels observed at these loci.

  Study phs002066

• University of Miami Udall Center of Excellence Identification of Rare Variants in PD through Whole Exome Sequencing

  The focus of this study is to identify a new level of genetic variation, i.e. rare genetic variants with a population frequency less than 5%, usually less than 1%, which are believed to provide a stronger risk per variant than those studied to date in the large genome wide association studies (GWAS). To do this we are generating whole exome sequencing data on the Illumina HiSeq. Each HiSeq produces at least 600 billion base pairs of DNA sequence in one run. Whole exome sequencing sequence data, about 50 million base pairs, or about 1.5% of the total DNA of each person's genome, is generated. We are using this data to look for new DNA variations that give risk for Parkinson disease, as well as "modifiers", that may lead to having more severe or milder disease or later or earlier ages of onset.

  Study phs000908

• Genetic Determinants of EGFR-Driven Lung Cancer Growth and Therapeutic Response In Vivo

  Oncogenic alterations in EGFR frequently co-occur with additional genetic alterations in EGFR-driven lung adenocarcinoma (LUAD), but how specific combinations of mutations affect tumor phenotypes and responses to targeted therapy is yet unknown. We leveraged a genetically engineered mouse model of EGFR mutant/Trp53-deficient LUAD to study the consequences of inactivating 10 different tumor suppressor genes on the fitness and tyorosine kinase inhibitor (TKI) sensitivity of these tumors. We found that loss of Keap1 is associated with a reduced response to therapy. In patients, we found that mutations in the KEAP1/NFE2L2/CUL3 pathway are associated with a significantly shorter time to treatment failure for EGFR TKI therapy compared to matched patients with wild-type KEAP1/NFE2L2/CUL3 tumors. We also analyzed whole exome sequencing data from tumor specimens before TKI treatment and at the time of treatment resistance for mutations in the KEAP1 pathway and these data are being submitted here.  

  Study phs002334

• GeneScreen, a Population Based, Targeted Genomic Screening Study

  The GeneScreen research study was based at the University of North Carolina (UNC) at Chapel Hill. It brought together researchers from different disciplines, including genetics, clinical medicine, bioethics, sociology, anthropology, psychology, and public health, to study the best ways to offer targeted genetic screening to the general adult population. DNA samples were collected from people who joined GeneScreen to look at a targeted panel of 17 genes. It tested for genetic differences (called mutations) that can cause one of 11 rare, but preventable or treatable conditions, including certain types of cancer and heart disease. Each condition has specific medical advice people can follow with their doctors to prevent or treat a serious health problem. The GeneScreen study was approved by the UNC Institutional Review Board and by the Kaiser Permanente Center for Health Research Institutional Review Board. GeneScreen is funded by the National Human Genome Research Institute of the National Institutes of Health.

  Study phs001817

• Differential Transcription Start Site Usage in Brain-related Samples

  RNA-Seq is an effective method to study the transcriptome, but specialized methods are required to identify 5' ends of transcripts. Several published strategies exist for this specific purpose, but their relative merits have not been systematically analyzed. Here, we directly compare the performance of six such methods - testing five with cellular RNA as well as a novel spike-in RNA assay that helps address interpretation challenges that arise from uncertainties in annotation or RNA processing. Using a single human RNA sample, we constructed and sequenced 18 libraries with these methods and one standard, control RNA-Seq library. We find that the CAGE method performed best for mRNA and that most of its unannotated peaks are supported by evidence from other genomic methods. We then applied CAGE to eight brain-related samples and revealed sample-specific transcription start site (TSS) usage as well as a transcriptome-wide shift in TSS usage between fetal and adult brain.

  Study phs001463