evs.gs.washington.eduNHLBI Exome Sequencing Project (ESP)

NHLBI Exome Sequencing Project (ESP) Home Data Browser Data Usage and Release How to Use What’s New Contact and FAQ Downloads The goal of the NHLBI GO Exome Sequencing Project (ESP) is to discover novel genes and mechanisms contributing to heart, lung and blood disorders by pioneering the application of next-generation sequencing of the protein coding regions of the human genome across diverse, richly-phenotyped populations and to share these datasets and findings with the scientific community to extend and enrich the diagnosis, management and treatment of heart, lung and blood disorders. The groups participating and collaborating in the NHLBI GO ESP include: Seattle GO - University of Washington, Seattle, WA Broad GO - Broad Institute of MIT and Harvard, Cambridge, MA WHISP GO - Ohio State University Medical Center, Columbus, OH Lung GO - University of Washington, Seattle, WA WashU GO - Washington University, St. Louis, MO Heart GO - University of Virginia Health System, Charlottesville, VA ChargeS GO - University of Texas Health Sciences Center at Houston The group includes some of the largest well-phenotyped populations in the United States, representing more than 200,000 individuals altogether from the: Women’s Health Initiative (WHI) Framingham Heart Study (FHS) Jackson Heart Study (JHS) Multi-Ethnic Study of Atherosclerosis (MESA) Atherosclerosis Risk in Communities (ARIC) Coronary Artery Risk Development in Young Adults (CARDIA) Cardiovascular Health Study (CHS) Lung Health Study (LHS) COPD Genetic Epidemiology (COPDGene) Severe Asthma Research Project (SARP) Pulmonary Arterial Hypertension population (PAH) Acute Lung Injury cohort (ALI) Cystic Fibrosis cohort (CF) PennCATH Cleveland Clinic Genebank Massachusetts General Hospital Premature Coronary Artery Disease Study (MGH PCAD) Heart Attack Risk in Puget Sound (HARPS) Translational Research Underlying Disparities in Myocardial Infarction Patients’ Health Status (TRIUMPH) Target :  examples of valid input for targets (one target per query): Gene HUGO : ACTB Gene ID : 60 Chr. Region : 1 : 1000000-1100000 Single Chr. Location : 7 : 5567417 rsID : rs71531321 Data Usage We request that any use of data obtained from the NHLBI GO ESP be cited in publications. Citation , NHLBI GO Exome Sequencing Project (ESP), Seattle, WA (URL: http://evs.gs.washington.edu/EVS/) [date (month, yr) accessed]. Acknowledgment for Publication The authors would like to thank the NHLBI GO Exome Sequencing Project and its ongoing studies which produced and provided exome variant calls for comparison: the Lung GO Sequencing Project (HL-102923), the WHI Sequencing Project (HL-102924), the Broad GO Sequencing Project (HL-102925), the Seattle GO Sequencing Project (HL-102926) and the Heart GO Sequencing Project (HL-103010). Public Data Release The current EVS data release ( ESP6500SI-V2 ) is taken from 6503 samples drawn from multiple ESP cohorts and represents all of the ESP exome variant data. Sequences were aligned to NCBI build 37 human genome reference using BWA. PCR Duplicates were removed using Picard. Alignments were recalibrated using GATK. Lane-level indel realignments and base alignment quality (BAQ) adjustments were applied. All data were simultaneously analyzed for exome SNP variants at the University of Michigan (by the Abecasis Laboratory). SNPs were called using a two-step approach. First, genotype likelihood files (GLFs) were generated using samtools pileup on individual BAM files. Next, we used glfMultiples, a multi-sample variant caller, to generate initial SNP calls. Details of the likelihood model implemented in glfMultiples are given in Li et al (Genome Research (2011) 21:940-951; section entitled "Identifying Potential Polymorphic Sites"). The Michigan SNP calling pipeline is available at: http://genome.sph.umich.edu/wiki/UMAKE . This pipeline makes diploid calls for pseudo-autosomal regions of male samples and haploid calls for the rest of the chromosome. Female samples have diploid calls for all regions on the X chromosome. SNPs were filtered by a machine-learning technique called support vector machine (SVM) classification (for a detailed description, see Filter Status ). Small INDEL variants were analyzed at the Broad Institute (by the Genome Sequencing and Analysis group) using the GATK variation discovery pipeline following the guidelines in the GATK best practices v4 . More specifically, each BAM was reduced to create a Reduced BAM, and then INDELs were discovered by analyzing all samples simultaneously with the GATK UnifiedGenotyper , and subsequently filtered by the GATK Variant Quality Score Recalibration (VQSR) filtering model, again following the V4 best practices. The INDEL genotypes for the X and Y chromosomes were adjusted to be consistent with the samples’ genders. Female samples have diploid calls for all regions on the X chromosome. Male samples have diploid calls for the pseudo-autosomal regions on the X chromosome and haploid calls for the rest of the X chromosome and on the Y chromosome as well. However, the INDEL calls for the ESP data are preliminary and not as robust as the SNP calls at this point, users are advised to keep this difference in mind when applying the ESP data to research studies. All SNPs and INDELs were further annotated by SeattleSeqAnnotation137 , and the variant annotations at the coding-DNA and protein levels follow mostly the HGVS conventions. A subset of this data ( ESP2500 ) that has more stringent filtering criteria is available in the latest release of dbSNP (build 134), and published by the ESP Population Genetics and Statistical Analysis Working Group. ( publication ) Terms of Service This web site is designed to disseminate exome sequencing data generated through federal funding from the NHLBI. This data is provided free-of-charge, provided the following permission statement is followed. There may be other information on the site, such as links to other sites, references to other project groups and federal grants. The University of Washington has no responsibility for these links and information. Permission The contents of the NHLBI ESP web site are intended for educational or research purposes. As stated above, a subset of exome variants on this website have been deposited in dbSNP , and the full dataset will be deposited in dbGaP as part of the ESP cohort data. We place no restrictions on the use of the data available from the EVS. You may download or copy the content and other downloadable items displayed on the portion of the web site, provided that in using the data, you follow the citation format given above. How to Use the Data Browser The current release has been tested successfully with Firefox (v.20.0), Chrome (v.26.0), Safari (v.5.0) and IE (v.10.0 and v.9.0). To use this site, your browser must have cookies and JavaScript enabled. The gene model is that of NCBI, June 2012. Chromosome positions are those of NCBI build 37 (UCSC hg19). 1. Search Type There are four ways to query variations: A. gene name (HUGO, upper or lower case) B. gene ID (from NCBI Entrez Gene ) C. chromosomal location D. dbSNP rs ID When a search by gene name or gene ID is made, there are sometimes alternative transcripts. A region large enough to cover all transcripts is chosen. 2. Select Data Two types of data, variant information and sequencing coverage information, are ouput under separated tabs. The variant data are summarized by European American and African American populations. Select the populations you are interested in to display. 3. Display Results Once the data sets are chosen, you can query variants using the ""display snp summary" button to aquire calculated values and annotations for the variants. The page "variant Summary Columns" details the quantities displayed. 4. Download Results Both variant and coverage data can be downloaded using the downloading option listed on the top of the diaplying pages. variant data can be downloaded in either text or...