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International coordination of large-scale human induced pluripotent stem cell initiatives: Wellcome Trust and ISSCR workshops white paper.

ABSTRACT: There is growing recognition of the potential value of human induced pluripotent stem cells (hiPSC) for understanding disease and identifying drugs targets. This has been reflected in the establishment of multiple large-scale hiPSC initiatives worldwide. Representatives of these met recently at a workshop supported by the Welcome Trust in the UK and in a focus session at the 2014 ISSCR annual meeting in Vancouver. The purpose was to discuss strategies for making thousands of hiPSC lines widely available with as few restrictions as possible while retaining financial viability and donor privacy. The outcome of these discussions is described here.

SUBMITTER: Soares FA

PROVIDER: S-EPMC4263998 | biostudies-literature |

REPOSITORIES: biostudies-literature

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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.

| S-EPMC2384233 | biostudies-literature

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.

| S-EPMC3551227 | biostudies-literature

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

The 2019 and 2021 International Workshops on Alport Syndrome.

Project description: Not available

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Analysis of differences in human leukocyte antigen between the two Wellcome Trust Case Control Consortium control datasets.

Project description:The Wellcome Trust Case Control Consortium (WTCCC) study was a large genome-wide association study that aimed to identify common variants associated with seven diseases. That study combined two control datasets (58C and UK Blood Services) as shared controls. Prior to using the combined controls, the WTCCC performed analyses to show that the genomic content of the control datasets was not significantly different. Recently, the analysis of human leukocyte antigen (HLA) genes has become prevalent due to the development of HLA imputation technology. In this project, we extended the between-control homogeneity analysis of the WTCCC to HLA. We imputed HLA information in the WTCCC control dataset and showed that the HLA content was not significantly different between the two control datasets, suggesting that the combined controls can be used as controls for HLA fine-mapping analysis based on HLA imputation.

| S-EPMC6808636 | biostudies-literature

Replication of the Wellcome Trust genome-wide association study of essential hypertension: the Family Blood Pressure Program.

Project description:Essential hypertension is a principal cardiovascular risk factor whose origin remains unknown. Classical genetic studies have shown that blood pressure is at least partially heritable, opening a window to understanding the pathophysiology of essential hypertension in the human using modern genetic tools. The Wellcome Trust Case Control Consortium has recently published the results of screening the genomes of 2000 essential hypertension cases and 3000 controls using 500 000 genome-wide single nucleotide polymorphisms (SNPs). None of the variants proved to be genome-wide significant after correction for multiple tests but the most significantly associated SNPs (P<10(-5)) constitute a priority list that warrant follow-up in other studies. We describe here replication studies of the top six SNPs in subjects from the US National Heart, Lung, and Blood Institute funded Family Blood Pressure Program comprising 11 433 individuals recruited by hypertensive families. The results suggest that only one of the six SNPs might be associated with essential hypertension in Americans of European origin. This SNP shows a significant but opposite effect in Americans of Hispanic origin and no association in African Americans. The significance of the opposing effect estimates is unclear. No replication could be shown for hypertension status, but there are differences in study design. This attempted replication highlights that essential hypertension studies will require more comprehensive and larger genetic screens.

| S-EPMC2585612 | biostudies-literature

1000 Genomes-based imputation identifies novel and refined associations for the Wellcome Trust Case Control Consortium phase 1 Data.

Project description:We hypothesize that imputation based on data from the 1000 Genomes Project can identify novel association signals on a genome-wide scale due to the dense marker map and the large number of haplotypes. To test the hypothesis, the Wellcome Trust Case Control Consortium (WTCCC) Phase I genotype data were imputed using 1000 genomes as reference (20100804 EUR), and seven case/control association studies were performed using imputed dosages. We observed two 'missed' disease-associated variants that were undetectable by the original WTCCC analysis, but were reported by later studies after the 2007 WTCCC publication. One is within the IL2RA gene for association with type 1 diabetes and the other in proximity with the CDKN2B gene for association with type 2 diabetes. We also identified two refined associations. One is SNP rs11209026 in exon 9 of IL23R for association with Crohn's disease, which is predicted to be probably damaging by PolyPhen2. The other refined variant is in the CUX2 gene region for association with type 1 diabetes, where the newly identified top SNP rs1265564 has an association P-value of 1.68 × 10(-16). The new lead SNP for the two refined loci provides a more plausible explanation for the disease association. We demonstrated that 1000 Genomes-based imputation could indeed identify both novel (in our case, 'missed' because they were detected and replicated by studies after 2007) and refined signals. We anticipate the findings derived from this study to provide timely information when individual groups and consortia are beginning to engage in 1000 genomes-based imputation.

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Launch of the Sao Paulo Wellcome Trust-funded multidisciplinary research program on optimising antimicrobial use in highly populated urban environments

Project description: Not available

| S-EPMC10460985 | biostudies-literature

Wellcome Trust Sanger Institute

Project description:Wellcome Trust Sanger Institute

| EGAC00001000205 | EGA

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

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