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• Conserved interferon-gamma signaling and decreased immune exclusion programs in responses to immune checkpoint blockade therapy_CM38-RNA

  We analyzed baseline and on-therapy tumor biopsies from 101 patients with advanced melanoma treated with nivolumab (anti-PD-1) alone or combined with ipilimumab (anti-CTLA-4). Analysis of whole transcriptome data showed that T cell infiltration and interferon-gamma signaling signatures corresponded most highly with clinical response to therapy, with a reciprocal decrease in cell cycle and WNT signaling pathways in responding biopsies. Clinical outcome differences were likely not due to differential melanoma cell responses to interferon-gamma, as 57 human melanoma cell lines exposed in vitro to this cytokine showed a conserved interferon-gamma transcriptome response unless they had mutations that precluded signaling from the interferon-gamma receptor. Therefore, the magnitude of the antitumor T cell response and the corresponding downstream interferon-gamma signaling are the main drivers of clinical response or resistance to immune checkpoint blockade therapy.

  Dataset EGAD00001006282

• Whole-genome sequencing in 14 cases and whole-exome sequencing in 90 cases of Chinese ESCC

  Esophageal cancer is one of the most aggressive cancers and the sixth leading cause of cancer death worldwide1. Approximately 70% of the global esophageal cancers occur in China and over 90% histopathological forms of this disease are esophageal squamous cell carcinoma (ESCC)2-3. Currently, there are limited clinical approaches for early diagnosis and treatment for ESCC, resulting in a 10% 5-year survival rate for the patients. Meanwhile, the full repertoire of genomic events leading to the pathogenesis of ESCC remains unclear. Here we show a comprehensive genomic analysis in 158 ESCC cases, as part of the International Cancer Genome Consortium (ICGC) Research Projects (http://icgc.org/icgc/cgp/72/371/1001734). We conducted whole-genome sequencing in 14 ESCC cases and whole-exome sequencing in 90 cases.

  Dataset EGAD00001001691

• Comparison of transcriptional response of induced pluripotent stem (iPS) cell-derived and monocyte-derived macrophages to bacterial lipopolysaccharide stimulation

  In the first part of this project, we will differentiate IPS cells from 5 human donors into macrophages, and extract RNA from unstimulated and LPS stimulated macrophages to perform RNA sequencing. We will also extract RNA before and after stimulation in blood- derived macrophages from 5 additional, unrelated healthy samples. In the second part of the project, RNA-seq data will be analysed to compare LPS response of these two macrophage populations. In summary, we will perform 75bp PE RNA-seq on 20 samples (10 pre and post stimulus), on the HiSeq 2500 platform. Samples will be multiplexed at 5 samples / lane, so we will require 4 flow cells in total.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 EGAD00001001106

• Next Generation Sequencing in an IBD Pedigree Whole Genome Data

  In 2009 we identified a four-generation family with over 700 members and 41 affected with Crohn's disease (CD). At the time we sequenced the exome of 6 affected individuals but did not identify any coding variants which appear to explain the high prevalence of disease. Since then we have collected DNA from a large number of additional family members, genotyped linkage arrays on the entire family to refine genomic regions shared by identity by descent and genotyped affected and unaffected members at known CD risk loci identified by Genome Wide Association Studies (GWAS). These analyses have confirmed that a significant unexplained excess of disease remains after accounting for all known genetic factors, and that several regions of the genome are shared by a large fraction of affected individuals. We therefore perform whole genomes sequencing from 8 individuals which will allow us to impute the complete sequence of nearly all the members of the two largest and most severely affected branches of the family.

  Dataset EGAD00001000399

• Chromosome Segregation Errors Promote a Diverse Spectrum of Simple and Complex Genomic Rearrangements

  Cancer genomes are frequently characterized by numerical and structural karyotypic abnormalities. Here we combined an inducible centromere-specific inactivation approach with selection for a conditionally essential gene, a strategy we term ‘CEN-SELECT’, and show that single-chromosome missegregation during cell division can directly drive a broad spectrum of structural rearrangement types. Cytogenetic profiling revealed that missegregated chromosomes are 120-fold more susceptible to developing seven major categories of structural variants, including translocations, insertions, deletions, and reassembly into chromothriptically rearranged chromosomes. Whole-genome sequencing of clones with genetically propagatable derivative chromosomes identified complex rearrangements and copy-number alterations that can result in gene inactivation or extrachromosomal gene amplification. We conclude that chromosome segregation errors are sufficient to drive extensive structural variation that recapitulates those commonly associated with human cancers.

  Dataset EGAD00001004163

• scRNA-Seq & scATAC-Seq Feature-counting Results Derived from 10X Cellrange-arc-count pipeline

  The feature-counting outputs from Cellrange-arc-count pipeline contain information at the single cell level, jointly for both scRNA-Seq and scATAT-Seq on 103 DLBCL samples and 3 normal controls (Please note that sc-40 only has scRNA-Seq data without scATAC-Seq). These files can be used as the input files for further downstream analysis software (e.g. Seurat Package). Moreover, a matrix of single-cell barcodes and associated cell biological types (used in the study) is also provided for users’ reference. This dataset is large and split into two parts to facilitate downloads. This dataset is large and split into two parts to facilitate downloads. The Linux command line of "tar -xvf xxxx_PART1.gz" should be used to extract the individual files. For additional information regarding the genomic data associated with the study, please also see the paper companion website at https://llmpp.ccr.cancer.gov/local/DLBCL_singlecell/

  Dataset EGAD50000002490

• Korea Epigenome Project(KEP), Korea National Research Institute of Health(KNIH)

  The KEP was launched in 2012 to produce 50 epigenomic sets on Korean chronic diseases related target cells with the participation on Internationsl Human Epigenome Consortium(IHEC) of which focus is constructing 1000 reference epigenome map on 250 human cell type. The objective of the KEP was to provide a comprehensive epigenomic map of Korean chronic disease-related target tissues. Single cells were isolated from the pancreas, fat and kidney. Islet, ductal, acinar, and beta cells from the pancreas were purified into a single homogenous cell type using flow-assisted cell sorting technique. Adipocytes and pre-adipocytes were purified from fat, using Percoll gradient centrifugation technique. Mesangial, distal tubule, proximal tubule, podocytes, and collecting duct cells from the kidney were collected using mechanical sieving and immunostaining methods. Each cell type was derived from normal tissue or those with diabetes, obesity, or chronic kidney disease. Sixty reference epigenome datasets of pancreatic, fat, kidney cells were produced. Cell types such as the islets, and beta from the pancreas, adipocytes, pre-adipocytes from fat tissue, podocyte, mesangial, tubules from kidney were used for primary target to produce a Korean metabolic reference epigenome. And the bisulfite converted-whole genome sequencing, Infinium 450k DNA methylation bead array, mRNA, miRNA-Sequencing were performed to produce a comprehensive epigenomic map. The aim of roadmap reports is preparation of Long-term and Mid-term Technology Roadmaps for Korean Human Epigenome Project towards a competitive execution of International Epigenome Project and successful expansion of the research outcomes. Roadmap reports reviewed on recent technological development of DNA methylation and histone modification analysis, emerging new trends in epigenome medicine, plans for hardware and software analysis systems aimed to epigenome analysis, medical expert opinion on target cells and isolation scheme, bioinformatics expert opinion on analytical tools, new ideas for a putative epigenome studies, trends in single cell epigenome analysis. In conclusion, roadmap report suggested several projects for the future KNIH epigenome research in collaboration with epigenome research group. These are including refocusing the goals of KNIH-driven research in identification of disease mechanism, development of new studies on GWAS-EWA, higher priority on the epigenomic studies of human primary cells, establishment of collaborative relationship with tissue banking centers, establishment of mapping centers and data analysis portals, establishment of Korean Epigenome Research Consortium, establishment of steering committee governing both research and funding, launching of additional funding for epigenomic researches.

  Study EGAS00001001774

• Copy Number Arrays

  Copy Number Alterations arrays from 21 patients and 24 samples performed by Affymetrix 6.0, Agilent 1M and Oncoscan CNV platforms

  Dataset EGAD00010001581

• 28 RNA-Seq from CAF-S1, CAF-S4 and EPCAM cells coming from Primary tumors and Lymph nodes of 5 patients)

  Dataset EGAD00001005744

• PE-META-CENTRAL_ASIA-FETAL

  Fixed effect meta-analysis summary statistics combining GWAS of fetal (baby) preeclampsia cases and controls from Central Asia (Kazakhstan and Uzbekistan).

  Dataset EGAD00010001987