Institution
Wellcome Trust Centre for Human Genetics
Facility•Oxford, United Kingdom•
About: Wellcome Trust Centre for Human Genetics is a facility organization based out in Oxford, United Kingdom. It is known for research contribution in the topics: Population & Genome-wide association study. The organization has 2122 authors who have published 4269 publications receiving 433899 citations.
Topics: Population, Genome-wide association study, Single-nucleotide polymorphism, Locus (genetics), Linkage disequilibrium
Papers published on a yearly basis
Papers
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TL;DR: The R/Bioconductor package scater is developed to facilitate rigorous pre‐processing, quality control, normalization and visualization of scRNA‐seq data and provides a convenient, flexible workflow to process raw sequencing reads into a high‐quality expression dataset ready for downstream analysis.
Abstract: Single-cell RNA sequencing (scRNA-seq) is increasingly used to study gene expression at the level of individual cells. However, preparing raw sequence data for further analysis is not a straightforward process. Biases, artifacts and other sources of unwanted variation are present in the data, requiring substantial time and effort to be spent on pre-processing, quality control (QC) and normalization.We have developed the R/Bioconductor package scater to facilitate rigorous pre-processing, quality control, normalization and visualization of scRNA-seq data. The package provides a convenient, flexible workflow to process raw sequencing reads into a high-quality expression dataset ready for downstream analysis. scater provides a rich suite of plotting tools for single-cell data and a flexible data structure that is compatible with existing tools and can be used as infrastructure for future software development.The open-source code, along with installation instructions, vignettes and case studies, is available through Bioconductor at http://bioconductor.org/packages/scater .davis@ebi.ac.uk.Supplementary data are available at Bioinformatics online.
1,093 citations
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TL;DR: This protocol presents a state-of-the-art computational and statistical RNA-seq differential expression analysis workflow largely based on the free open-source R language and Bioconductor software and, in particular, on two widely used tools, DESeq and edgeR.
Abstract: RNA sequencing (RNA-seq) has been rapidly adopted for the profiling of transcriptomes in many areas of biology, including studies into gene regulation, development and disease. Of particular interest is the discovery of differentially expressed genes across different conditions (e.g., tissues, perturbations) while optionally adjusting for other systematic factors that affect the data-collection process. There are a number of subtle yet crucial aspects of these analyses, such as read counting, appropriate treatment of biological variability, quality control checks and appropriate setup of statistical modeling. Several variations have been presented in the literature, and there is a need for guidance on current best practices. This protocol presents a state-of-the-art computational and statistical RNA-seq differential expression analysis workflow largely based on the free open-source R language and Bioconductor software and, in particular, on two widely used tools, DESeq and edgeR. Hands-on time for typical small experiments (e.g., 4-10 samples) can be <1 h, with computation time <1 d using a standard desktop PC.
1,029 citations
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TL;DR: It is shown that extracts from VHL-deficient renal carcinoma cells have a defect in HIF-α ubiquitylation activity which is complemented by exogenous pVHL, and this defect was specific for Hif-α among a range of substrates tested.
1,026 citations
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Kyriaki Michailidou1, Kyriaki Michailidou2, Sara Lindström3, Sara Lindström4 +393 more•Institutions (127)
TL;DR: A genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry finds that heritability of Breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2–5-fold enriched relative to the genome- wide average.
Abstract: Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10-8. The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.
1,014 citations
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TL;DR: Endometriosis impairs HRQoL and work productivity across countries and ethnicities, yet women continue to experience diagnostic delays in primary care, and a higher index of suspicion is needed to expedite specialist assessment of symptomatic women.
1,007 citations
Authors
Showing all 2127 results
Name | H-index | Papers | Citations |
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Mark I. McCarthy | 200 | 1028 | 187898 |
John P. A. Ioannidis | 185 | 1311 | 193612 |
Gonçalo R. Abecasis | 179 | 595 | 230323 |
Simon I. Hay | 165 | 557 | 153307 |
Robert Plomin | 151 | 1104 | 88588 |
Ashok Kumar | 151 | 5654 | 164086 |
Julian Parkhill | 149 | 759 | 104736 |
James F. Wilson | 146 | 677 | 101883 |
Jeremy K. Nicholson | 141 | 773 | 80275 |
Hugh Watkins | 128 | 524 | 91317 |
Erik Ingelsson | 124 | 538 | 85407 |
Claudia Langenberg | 124 | 452 | 67326 |
Adrian V. S. Hill | 122 | 589 | 64613 |
John A. Todd | 121 | 515 | 67413 |
Elaine Holmes | 119 | 560 | 58975 |