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• Clonal_selection_after_gene_therapy_in_SCD___Duplex_sequencing

  This study includes the targeted duplex sequencing data relating to this study. A custom targeted panel was used including 29 AML-associated genes, and a set of mutations from driver-containing clones that were sequenced during the WGS tree-building phase of the study. Targeted sequencing is performed on each of 6 individuals included at the study at at least 3 time points per individual: one prior to gene therapy, and two post-therapy time points.

  Study EGAS00001007253

• GWAS on covid-19 severity and susceptibility in the province of Bergamo, Italy

  This is a case-control GWAS that involved the voluntary recruitment of inhabitants of the Bergamo province via an online questionnaire. We collected detailed clinical data and verified all information through personal interviews. Cases (severe COVID-19; G1) and controls (mild or asymptomatic COVID-19, G2; non-infected, G3) were matched by age, sex and risk factors

  Study EGAS00001007310

• To_profile_the_landscape_of_sebaceous_tumours___RNA

  Sebaceous tumours are a rare cutaneous cancer with potential for aggressive behaviour. However, limited information is available on these cancers with few published cases. Here we wish to exome sequence these cancers to define the first genomic landscape for this malignancy. We will extract RNA from formalin-fixed, paraffin-embedded (FFPE) cores. Cores may be obtained from lesional and non-lesional tissues of primaries as well as matching metastases. The extracted RNA will be used for RNA sequencing.

  Study EGAS00001007803

• Myeloma Genome Project Targeted Sequencing Panel - Oxford Data

  This dataset comprises the BAM files from targeted genome sequencing of CD138+ selected myeloma tumour samples from 21 individuals. In 5 cases there is only one tumour sample, but in the other 16 cases there are sequential samples, spanning treatment relapses. There are denoted Tumor A, B C etc. Therefore there are a total of 48 myeloma tumour samples. For each individual there is also a germline control samples, obtained either from peripheral blood or from CD138-selected bone marrow cells.

  Dataset EGAD00001008735

• RNA stability controlled by m6A methylation contributes to X-to-autosome dosage compensation in mamals

  In mammals, X-chromosomal genes are expressed from a single copy since males (XY) possess a single X chromosome, while females (XX) undergo X inactivation. To compensate for this reduction in dosage compared to two active copies of autosomes, it has been proposed that genes from the active X chromosome exhibit dosage compensation. However, the existence and mechanism of X-to-autosome dosage compensation are still under debate. Here, we show that X-chromosomal transcripts are reduced in m6A modifications and more stable compared to their autosomal counterparts. Acute depletion of m6A selectively stabilises autosomal transcripts, resulting in perturbed dosage compensation in mouse embryonic stem cells. We propose that higher stability of X-chromosomal transcripts is directed by lower levels of m6A, indicating that mammalian dosage compensation is partly regulated by epitranscriptomic RNA modifications.

  Dataset EGAD00001010194

• Low coverage whole-genome sequencing of samples from the Cretan Greek isolate collection HELIC-MANOLIS

  Whole-genome sequencing at 1x of samples from the Cretan Greek isolate collection HELIC-MANOLIS. Genome-wide association studies of complex traits have been successful in identifying common variant associations, but a substantial heritability gap remains. The field of complex trait genetics is shifting towards the study of low frequency and rare variants, which are hypothesised to have larger effects. The study of these variants can be empowered by focusing on isolated populations, in which rare variants may have increased in frequency and linkage disequilibrium tends to be extended. This work focuses on an isolated population from Crete, Greece. Sequencing is very efficient in isolated populations, because variants found in a few samples will be shared by others in extended haplotype contexts, supporting accurate imputation.

  Dataset EGAD00001001637

• Identification of genes involved in congenital disorders of glycosylation and 3-methylglutaconic aciduria (2018-03-14)

  Identification of genes involved in congenital disorders of glycosylation and 3-methylglutaconic aciduria. There are more than 100 genes known for congenital disorders of glycosylation and new disorders are discovered each year. WE included patients with a so far unsolved glycosylation disease. The diagnostic group 3-methyglutaconic aciduria is a heterogenous group of disorders mostly caused by abnormal phospholipid synthesis or in association with mitochondrial dysfunction. We included patients with a so far unsolved disease and 3-methylglutaconic aciduria. 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 2018-03-14.

  Dataset EGAD00001004038

• Whole exome sequencing for clarification of rare causes of axonal Charcot-Marie-Tooth disease (2017-08-16)

  The project is focused on the axonal forms of Charcot-Marie-Tooth (CMT) disease. We have selected 13 families (7 from Spain and 6 from Czech Republic) that have been indepth clinically assessed and previously tested for mutations in known CMT genes without causal variants characterised. In these patients we expect to discover several CMT2 genes. Thus, we requested for exome sequencing of 45 DNAs:27 exomes in families from Spain and 18 exomes in the families from Czech Republic. 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 2017-08-16.

  Dataset EGAD00001003565

• Genome Diversity in Africa Project - ancient samples - standard libraries

  Given the central importance of Africa to studies of human origins, genetic diversity and disease susceptibility, large-scale and representative characterisation of genetic diversity in Africa is needed. Analyses of ancient DNA from Africa would complement sequencing of modern African populations and provide unique opportunities to transform our understanding of the pre-history of the region. This approach would greatly refine our understanding of population structure and gene flow in Africa and globally, including genetic signatures of ancient admixture. This low coverage sequencing experiment will allow us to test and refine our pipeline for ancient DNA 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 EGAD00001002211

• Genomic Signatures of Intestinal Metaplasia in Six Countries with Varying Incidence of Stomach Cancer

  Intestinal metaplasia (IM) is a pre-cancerous condition associated with gastric cancer (GC), a deadly malignancy with varying geographic incidence. Performing a genomic analysis of over 1,500 IM samples from six countries, we identified 46 significantly mutated genes. We observed IM driver genes associated with high-risk populations and worse prognosis (ARID1A), members of the KRAS/MAPK signalling pathway (KRAS, BRAF, MAP2K1, MAP3K1, MAP2K4, NF1), and altered mucosal immunity (PIGR).

  Study EGAS50000001056

• Genome-wide DNA Methylation Data from Illumina HumanMethylationEPIC arrays for whole blood samples from 403 healthy individuals

  Genome-wide DNA Methylation Data from Illumina HumanMethylationEPIC arrays for whole blood samples from 403 healthy individuals. Additional associated phenotype information is available for all individuals included in this study directly from CIBMTR. Data are available under controlled access release upon reasonable request and execution of a data use agreement. Requests should be submitted to CIBMTR at info-request@mcw.edu and include the study reference IB17-04.

  Study EGAS00001006033

• DNA-Sequencing of Baseline Plasma From the Phase III Alliance A031201 Trial

  Liquid biopsy assays tailored for metastatic castration-resistant prostate cancer (mCRPC) patients are needed to identify molecular alterations and predict survival in the context of androgen receptor (AR) inhibitors. We developed a novel plasma cell-free DNA (cfDNA) sequencing assay to detect circulating tumor DNA (ctDNA) and alterations in key mCRPC driver genes, and tested associations with clinical features and survival outcomes in a phase III trial. cfDNA was isolated from evaluable baseline plasma specimens of untreated mCRPC patients (n=790) enrolled in the Alliance A031201 randomized phase III trial (NCT01949337) prior to enzalutamide therapy with or without abiraterone acetate and prednisone. A customized targeted cfDNA sequencing assay was used to detect AR and non-AR alterations in mCRPC. For this, DNA-seq libraries were constructed from cfDNA using Takara ThruPLEX Tag-Seq or Plasma-Seq kits, and subjected to hybridization enrichment using a custom-designed Agilent SureSelect bait panel. Post-capture DNA-seq libraries were pooled and sequenced on an Illumina HiSeq 2500 using 2x150 bp settings. ctDNA positivity was defined as >20% ctDNA using an aneuploidy-based estimate derived from ichorCNA (Group 1) or a novel definition of ≤20% ctDNA, but with detection of any alteration in AR, or gain of MYC and/or MYCN (Group 2). cfDNA sequencing data was obtained from 776 patients. There were 480/776 (62%) ctDNA-positive patients, with 324 (42%) in Group 1 and an additional 156 (20%) in Group 2 with AR or MYC/MYCN alterations detected. ctDNA-positive patients in Groups 1 and 2 had similarly poor median overall survival (OS) of 25.4 months (95% CI: 21.8-29.0) and 29.7 months (95% CI: 27.3-35.5), respectively, as compared to ctDNA-negative patients who had a median OS of 49.1 months (95% CI: 42.3-53.5). Relative to ctDNA-negative patients, OS was inferior in ctDNA-positive patients in Group 1 (HR 2.3, 95% CI: 1.9-2.9, P AR inhibitors in a contemporary phase III trial.

  Study phs003325

• OA_knee-M-1

  Array methylation profiling of knee osteoarthritis patients who have undergone total joint replacement

  Dataset EGAD00010001287

• thraruk-G-1

  Resolving the Genetic Architecture of Aseptic Loosening After Total Hip Replacement

  Dataset EGAD00010001289

• Identifying the role of ID3 in DNA repair and maintenance of genome integrity (ATAC-seq)

  Dataset EGAD00001008199

• Transcriptome of (peripheral blood), from donor Sample B, replicate 2 time-course biological replicates; 10x lane replicate 3

  time-course biological replicates; 10x lane replicate 3

  Dataset EGAD00001010093

• Transcriptome of (peripheral blood), from donor Sample B, replicate 2 time-course biological replicates; 10x lane replicate 2

  time-course biological replicates; 10x lane replicate 2

  Dataset EGAD00001010091

• uganda_X

  Genotype data (in binary PLINK format) and imputed data (with merged 1000Gp3 and AGVP reference panel in GEMMA BIMBAM dosage format) for 1391 individuals from EMaBS in Entebbe, Uganda - X chromosome.

  Dataset EGAD00010002583

• Whole genome sequencing of UM with MSI

  Illumina platform sequencing of whole genome libraries prepared from paired tumour/normal samples from 1 case of melanoma uveal with MSI

  Dataset EGAD50000001337

• Reference epigenome IPS-NPC02 input ChIP-Seq data generated from KEP study

  IPS-NPC02 input ChIP-Seq paired end data

  Dataset EGAD00001007290

• Reference epigenome Pancreas-Islet03 h3k27me3 ChIP-Seq data generated from KEP study

  Pancreas-Islet03 h3k27me3 ChIP-Seq paired end data

  Dataset EGAD00001007201

• Reference epigenome KNIH005 WGBS data generated from KEP study

  A KNIH005 Whole-Genome Bisulfite Sequencing(WGBS) paired end data for islet cells

  Dataset EGAD00001002753

• Reference epigenome Fat-Preadipocyte01 h3k36me3 ChIP-Seq data generated from KEP study

  Fat-Preadipocyte01 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007223

• Reference epigenome Fat-Preadipocyte01 h3k4me3 ChIP-Seq data generated from KEP study

  Fat-Preadipocyte01 h3k4me3 ChIP-Seq paired end data

  Dataset EGAD00001007225

• Reference epigenome Kidney-Podocyte01 h3k4me1 ChIP-Seq data generated from KEP study

  Kidney-Podocyte01 h3k4me1 ChIP-Seq paired end data

  Dataset EGAD00001007231

• Reference epigenome Kidney-mesangial02 h3k36me3 ChIP-Seq data generated from KEP study

  Kidney-mesangial02 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007258

• Reference epigenome Pancreas-Islet07 input ChIP-Seq data generated from KEP study

  Pancreas-Islet07 input ChIP-Seq paired end data

  Dataset EGAD00001007463

• Reference epigenome Pancreas-Islet07 h3k9me3 ChIP-Seq data generated from KEP study

  Pancreas-Islet07 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007462

• Reference epigenome Pancreas-Islet02 h3k9me3 ChIP-Seq data generated from KEP study

  Pancreas-Islet02 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007198

• Reference epigenome Pancreas-Islet02 input ChIP-Seq data generated from KEP study

  Pancreas-Islet02 input ChIP-Seq paired end data

  Dataset EGAD00001007199

• Reference epigenome Pancreas-Islet03 h3k27ac ChIP-Seq data generated from KEP study

  Pancreas-Islet03 h3k27ac ChIP-Seq paired end data

  Dataset EGAD00001007200

• Reference epigenome Kidney-Podocyte01 h3k27me3 ChIP-Seq data generated from KEP study

  Kidney-Podocyte01 h3k27me3 ChIP-Seq paired end data

  Dataset EGAD00001007229

• Reference epigenome IPS-Fibroblast02 h3k9me3 ChIP-Seq data generated from KEP study

  IPS-Fibroblast02 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007275

• Reference epigenome IPS-NPC02 h3k27ac ChIP-Seq data generated from KEP study

  IPS-NPC02 h3k27ac ChIP-Seq paired end data

  Dataset EGAD00001007284

• Reference epigenome IPS-ENeuron02 h3k4me3 ChIP-Seq data generated from KEP study

  IPS-ENeuron02 h3k4me3 ChIP-Seq paired end data

  Dataset EGAD00001007302

• Reference epigenome KNIH003 WGBS data generated from KEP study

  A KNIH003 Whole-Genome Bisulfite Sequencing(WGBS) paired end data for islet cells

  Dataset EGAD00001002751

• Reference epigenome Pancreas-Islet06 h3k36me3 ChIP-Seq data generated from KEP study

  Pancreas-Islet06 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007452

• Reference epigenome Pancreas-Islet06 h3k4me1 ChIP-Seq data generated from KEP study

  Pancreas-Islet06 h3k4me1 ChIP-Seq paired end data

  Dataset EGAD00001007453

• Reference epigenome Pancreas-Islet07 h3k4me3 ChIP-Seq data generated from KEP study

  Pancreas-Islet07 h3k4me3 ChIP-Seq paired end data

  Dataset EGAD00001007461

• Reference epigenome Pancreas-Islet04 h3k4me3 ChIP-Seq data generated from KEP study

  Pancreas-Islet04 h3k4me3 ChIP-Seq paired end data

  Dataset EGAD00001007211

• Reference epigenome Kidney-Podocyte03 h3k36me3 ChIP-Seq data generated from KEP study

  Kidney-Podocyte03 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007237

• Reference epigenome Pancreas-Islet08 h3k36me3 ChIP-Seq data generated from KEP study

  Pancreas-Islet08 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007466

• Reference epigenome Fat-adipocyte04 h3k27ac ChIP-Seq data generated from KEP study

  Fat-adipocyte04 h3k27ac ChIP-Seq paired end data

  Dataset EGAD00001007478

• Reference epigenome Pancreas-Islet08 h3k9me3 ChIP-Seq data generated from KEP study

  Pancreas-Islet08 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007469

• Reference epigenome Fat-adipocyte03 h3k27ac ChIP-Seq data generated from KEP study

  Fat-adipocyte03 h3k27ac ChIP-Seq paired end data

  Dataset EGAD00001007471

• Reference epigenome Fat-adipocyte04 input ChIP-Seq data generated from KEP study

  Fat-adipocyte04 input ChIP-Seq paired end data

  Dataset EGAD00001007484

• Reference epigenome Fat-adipocyte04 h3k4me1 ChIP-Seq data generated from KEP study

  Fat-adipocyte04 h3k4me1 ChIP-Seq paired end data

  Dataset EGAD00001007481

• Reference epigenome Fat-adipocyte04 h3k9me3 ChIP-Seq data generated from KEP study

  Fat-adipocyte04 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007483

• Reference epigenome Fat-adipocyte05 h3k27ac ChIP-Seq data generated from KEP study

  Fat-adipocyte05 h3k27ac ChIP-Seq paired end data

  Dataset EGAD00001007485

• Reference epigenome Fat-adipocyte05 h3k27me3 ChIP-Seq data generated from KEP study

  Fat-adipocyte05 h3k27me3 ChIP-Seq paired end data

  Dataset EGAD00001007486