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Omics score: 1003

The Wellcome Trust Sanger Institute (WTSI)

ABSTRACT: Organisation EGAO00000000080

PROVIDER: EGAO00000000080 | EGA |

REPOSITORIES: EGA

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The metabochip, a custom genotyping array for genetic studies of metabolic, cardiovascular, and anthropometric traits.

Voight Benjamin F BF Kang Hyun Min HM Ding Jun J Palmer Cameron D CD Sidore Carlo C Chines Peter S PS Burtt Noël P NP Fuchsberger Christian C Li Yanming Y Erdmann Jeanette J Frayling Timothy M TM Heid Iris M IM Jackson Anne U AU Johnson Toby T Kilpeläinen Tuomas O TO Lindgren Cecilia M CM Morris Andrew P AP Prokopenko Inga I Randall Joshua C JC Saxena Richa R Soranzo Nicole N Speliotes Elizabeth K EK Teslovich Tanya M TM Wheeler Eleanor E Maguire Jared J Parkin Melissa M Potter Simon S Rayner N William NW Robertson Neil N Stirrups Kathleen K Winckler Wendy W Sanna Serena S Mulas Antonella A Nagaraja Ramaiah R Cucca Francesco F Barroso Inês I Deloukas Panos P Loos Ruth J F RJ Kathiresan Sekar S Munroe Patricia B PB Newton-Cheh Christopher C Pfeufer Arne A Samani Nilesh J NJ Schunkert Heribert H Hirschhorn Joel N JN Altshuler David D McCarthy Mark I MI Abecasis Gonçalo R GR Boehnke Michael M

PLoS genetics 20120802 8

Genome-wide association studies have identified hundreds of loci for type 2 diabetes, coronary artery disease and myocardial infarction, as well as for related traits such as body mass index, glucose and insulin levels, lipid levels, and blood pressure. These studies also have pointed to thousands of loci with promising but not yet compelling association evidence. To establish association at additional loci and to characterize the genome-wide significant loci by fine-mapping, we designed the "Me ...[more]

PMID: 22876189

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Implementing a genomic data management system using iRODS in the Wellcome Trust Sanger Institute.

Project description:BackgroundIncreasingly large amounts of DNA sequencing data are being generated within the Wellcome Trust Sanger Institute (WTSI). The traditional file system struggles to handle these increasing amounts of sequence data. A good data management system therefore needs to be implemented and integrated into the current WTSI infrastructure. Such a system enables good management of the IT infrastructure of the sequencing pipeline and allows biologists to track their data.ResultsWe have chosen a data grid system, iRODS (Rule-Oriented Data management systems), to act as the data management system for the WTSI. iRODS provides a rule-based system management approach which makes data replication much easier and provides extra data protection. Unlike the metadata provided by traditional file systems, the metadata system of iRODS is comprehensive and allows users to customize their own application level metadata. Users and IT experts in the WTSI can then query the metadata to find and track data.The aim of this paper is to describe how we designed and used (from both system and user viewpoints) iRODS as a data management system. Details are given about the problems faced and the solutions found when iRODS was implemented. A simple use case describing how users within the WTSI use iRODS is also introduced.ConclusionsiRODS has been implemented and works as the production system for the sequencing pipeline of the WTSI. Both biologists and IT experts can now track and manage data, which could not previously be achieved. This novel approach allows biologists to define their own metadata and query the genomic data using those metadata.

| S-EPMC3228552 | biostudies-literature

Wellcome Trust Sanger Institute

Project description:The Wellcome Trust Sanger Institute (WTSI), Hinxton, Cambridge, UK is a not-for-profit research organisation and a world famous Genome Centre dedicated to the sequencing and functional analysis of genomes. The Sanger Institute underpins biological and medical research worldwide through large-scale analysis, focused research and collaborations. Genome sequence analysis is complemented by computational interpretation and experimental analysis of gene function in a variety of model organisms. There are designated teams for library preparation, sequencing production and data processing. The data centre for computation and data distribution has recently been extended and now has in excess of 4000 terabytes (Tb) of storage space available and a compute farm consisting of almost 5,000 CPUs.

| EGAO00000000020 | EGA

Wellcome Sanger Institute

Project description:Organisation EGAO00000001233

| EGAO00000001233 | EGA

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Project description:Wellcome Trust Sanger Institute

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Project description:Organisation EGAO00000000136

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Haplotypic analysis of Wellcome Trust Case Control Consortium data.

Project description:We applied a recently developed multilocus association testing method (localized haplotype clustering) to Wellcome Trust Case Control Consortium data (14,000 cases of seven common diseases and 3,000 shared controls genotyped on the Affymetrix 500 K array). After rigorous data quality filtering, we identified three disease-associated loci with strong statistical support from localized haplotype cluster tests but with only marginal significance in single marker tests. These loci are chromosomes 10p15.1 with type 1 diabetes (p = 5.1 x 10(-9)), 12q15 with type 2 diabetes (p = 1.9 x 10(-7)) and 15q26.2 with hypertension (p = 2.8 x 10(-8)). We also detected the association of chromosome 9p21.3 with type 2 diabetes (p = 2.8 x 10(-8)), although this locus did not pass our stringent genotype quality filters. The association of 10p15.1 with type 1 diabetes and 9p21.3 with type 2 diabetes have both been replicated in other studies using independent data sets. Overall, localized haplotype cluster analysis had better success detecting disease associated variants than a previous single-marker analysis of imputed HapMap SNPs. We found that stringent application of quality score thresholds to genotype data substantially reduced false-positive results arising from genotype error. In addition, we demonstrate that it is possible to simultaneously phase 16,000 individuals genotyped on genome-wide data (450 K markers) using the Beagle software package.

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WT Sanger Institute

Project description:Organisation EGAO00000000380

| EGAO00000000380 | EGA

An exhaustive epistatic SNP association analysis on expanded Wellcome Trust data.

Project description:We present an approach for genome-wide association analysis with improved power on the Wellcome Trust data consisting of seven common phenotypes and shared controls. We achieved improved power by expanding the control set to include other disease cohorts, multiple races, and closely related individuals. Within this setting, we conducted exhaustive univariate and epistatic interaction association analyses. Use of the expanded control set identified more known associations with Crohn's disease and potential new biology, including several plausible epistatic interactions in several diseases. Our work suggests that carefully combining data from large repositories could reveal many new biological insights through increased power. As a community resource, all results have been made available through an interactive web server.

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