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Institution

Wellcome Trust Sanger Institute

NonprofitCambridge, United Kingdom
About: Wellcome Trust Sanger Institute is a nonprofit organization based out in Cambridge, United Kingdom. It is known for research contribution in the topics: Population & Genome. The organization has 4009 authors who have published 9671 publications receiving 1224479 citations.


Papers
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Journal ArticleDOI
TL;DR: An extensive study of variability in genes encoding proteins that are believed to be involved in the action and biotransformation of warfarin finds that weaker associations observed for other genes could explain up to ∼10% additional dose variance, but require testing and validation in an independent and larger data set.
Abstract: We report an extensive study of variability in genes encoding proteins that are believed to be involved in the action and biotransformation of warfarin. Warfarin is a commonly prescribed anticoagulant that is difficult to use because of the wide interindividual variation in dose requirements, the narrow therapeutic range and the risk of serious bleeding. We genotyped 201 patients for polymorphisms in 29 genes in the warfarin interactive pathways and tested them for association with dose requirement. In our study, polymorphisms in or flanking the genes VKORC1, CYP2C9, CYP2C18, CYP2C19, PROC, APOE, EPHX1, CALU, GGCX and ORM1-ORM2 and haplotypes of VKORC1, CYP2C9, CYP2C8, CYP2C19, PROC, F7, GGCX, PROZ, F9, NR1I2 and ORM1-ORM2 were associated with dose (P < 0.05). VKORC1, CYP2C9, CYP2C18 and CYP2C19 were significant after experiment-wise correction for multiple testing (P < 0.000175), however, the association of CYP2C18 and CYP2C19 was fully explained by linkage disequilibrium with CYP2C9*2 and/or *3. PROC and APOE were both significantly associated with dose after correction within each gene. A multiple regression model with VKORC1, CYP2C9, PROC and the non-genetic predictors age, bodyweight, drug interactions and indication for treatment jointly accounted for 62% of variance in warfarin dose. Weaker associations observed for other genes could explain up to approximately 10% additional dose variance, but require testing and validation in an independent and larger data set. Translation of this knowledge into clinical guidelines for warfarin prescription will be likely to have a major impact on the safety and efficacy of warfarin.

383 citations

Journal ArticleDOI
05 Sep 2018-Nature
TL;DR: Analysis of blood from a healthy human show that haematopoietic stem cells increase rapidly in numbers through early life, reaching a stable plateau in adulthood, and contribute to myeloid and B lymphocyte populations throughout life.
Abstract: Haematopoietic stem cells drive blood production, but their population size and lifetime dynamics have not been quantified directly in humans Here we identified 129,582 spontaneous, genome-wide somatic mutations in 140 single-cell-derived haematopoietic stem and progenitor colonies from a healthy 59-year-old man and applied population-genetics approaches to reconstruct clonal dynamics Cell divisions from early embryogenesis were evident in the phylogenetic tree; all blood cells were derived from a common ancestor that preceded gastrulation The size of the stem cell population grew steadily in early life, reaching a stable plateau by adolescence We estimate the numbers of haematopoietic stem cells that are actively making white blood cells at any one time to be in the range of 50,000-200,000 We observed adult haematopoietic stem cell clones that generate multilineage outputs, including granulocytes and B lymphocytes Harnessing naturally occurring mutations to report the clonal architecture of an organ enables the high-resolution reconstruction of somatic cell dynamics in humans

383 citations

Journal ArticleDOI
Vanessa K. Wong1, Vanessa K. Wong2, Stephen Baker3, Stephen Baker4, Stephen Baker5, Derek Pickard2, Julian Parkhill2, Andrew J. Page2, Nicholas A. Feasey6, Robert A. Kingsley7, Robert A. Kingsley2, Nicholas R. Thomson2, Nicholas R. Thomson3, Jacqueline A. Keane2, François-Xavier Weill8, David J. Edwards9, Jane Hawkey9, Simon R. Harris2, Alison E. Mather2, Amy K. Cain2, James Hadfield2, Peter J. Hart10, Nga Tran Vu Thieu5, Elizabeth J. Klemm2, Dafni A. Glinos2, Robert F. Breiman11, Robert F. Breiman12, Robert F. Breiman13, Conall H. Watson3, Samuel Kariuki2, Samuel Kariuki11, Melita A. Gordon14, Robert S. Heyderman15, Chinyere K. Okoro2, Jan Jacobs16, Jan Jacobs17, Octavie Lunguya, W. John Edmunds3, Chisomo L. Msefula15, José A. Chabalgoity18, Mike Kama, Kylie Jenkins, Shanta Dutta, Florian Marks19, Josefina Campos, Corinne N. Thompson4, Corinne N. Thompson5, Stephen K. Obaro, Calman A. MacLennan2, Calman A. MacLennan20, Calman A. MacLennan10, Christiane Dolecek5, Karen H. Keddy21, Anthony M. Smith21, Christopher M. Parry3, Christopher M. Parry22, Abhilasha Karkey23, E. Kim Mulholland3, James Campbell5, James Campbell4, Sabina Dongol23, Buddha Basnyat23, Muriel Dufour, Don Bandaranayake, Take Toleafoa Naseri, Shalini Singh24, Mochammad Hatta25, Paul N. Newton5, Paul N. Newton26, Robert S. Onsare11, Lupeoletalalei Isaia, David A. B. Dance26, David A. B. Dance5, Viengmon Davong26, Guy E. Thwaites4, Guy E. Thwaites5, Lalith Wijedoru27, John A. Crump28, Elizabeth de Pinna29, Satheesh Nair29, Eric J. Nilles24, Duy Pham Thanh5, Paul Turner30, Paul Turner27, Paul Turner5, Sona Soeng30, Mary Valcanis9, Joan Powling9, Karolina Dimovski9, Geoff Hogg9, Jeremy Farrar5, Jeremy Farrar4, Kathryn E. Holt9, Gordon Dougan2 
TL;DR: This whole-genome sequence analysis of Salmonella enterica serovar Typhi identifies a single dominant MDR lineage, H58, that has emerged and spread throughout Asia and Africa over the last 30 years, and identifies numerous transmissions of H58.
Abstract: The emergence of multidrug-resistant (MDR) typhoid is a major global health threat affecting many countries where the disease is endemic. Here whole-genome sequence analysis of 1,832 Salmonella enterica serovar Typhi (S. Typhi) identifies a single dominant MDR lineage, H58, that has emerged and spread throughout Asia and Africa over the last 30 years. Our analysis identifies numerous transmissions of H58, including multiple transfers from Asia to Africa and an ongoing, unrecognized MDR epidemic within Africa itself. Notably, our analysis indicates that H58 lineages are displacing antibiotic-sensitive isolates, transforming the global population structure of this pathogen. H58 isolates can harbor a complex MDR element residing either on transmissible IncHI1 plasmids or within multiple chromosomal integration sites. We also identify new mutations that define the H58 lineage. This phylogeographical analysis provides a framework to facilitate global management of MDR typhoid and is applicable to similar MDR lineages emerging in other bacterial species.

383 citations

Journal ArticleDOI
TL;DR: In this article, the suitability of these methods for single-cell transcriptomics has not been assessed and the authors discuss commonly used normalization approaches and illustrate how these can produce misleading results.
Abstract: Single-cell transcriptomics is becoming an important component of the molecular biologist's toolkit. A critical step when analyzing data generated using this technology is normalization. However, normalization is typically performed using methods developed for bulk RNA sequencing or even microarray data, and the suitability of these methods for single-cell transcriptomics has not been assessed. We here discuss commonly used normalization approaches and illustrate how these can produce misleading results. Finally, we present alternative approaches and provide recommendations for single-cell RNA sequencing users.

381 citations

Journal ArticleDOI
TL;DR: A software package that interfaces Mascot with Percolator, a well performing machine learning method for rescoring database search results, is presented and it is demonstrated to be amenable for both low and high accuracy mass spectrometry data.
Abstract: Sound scoring methods for sequence database search algorithms such as Mascot and Sequest are essential for sensitive and accurate peptide and protein identifications from proteomic tandem mass spectrometry data. In this paper, we present a software package that interfaces Mascot with Percolator, a well performing machine learning method for rescoring database search results, and demonstrate it to be amenable for both low and high accuracy mass spectrometry data, outperforming all available Mascot scoring schemes as well as providing reliable significance measures. Mascot Percolator can be readily used as a stand alone tool or integrated into existing data analysis pipelines.

381 citations


Authors

Showing all 4058 results

NameH-indexPapersCitations
Nicholas J. Wareham2121657204896
Gonçalo R. Abecasis179595230323
Panos Deloukas162410154018
Michael R. Stratton161443142586
David W. Johnson1602714140778
Michael John Owen1601110135795
Naveed Sattar1551326116368
Robert E. W. Hancock15277588481
Julian Parkhill149759104736
Nilesh J. Samani149779113545
Michael Conlon O'Donovan142736118857
Jian Yang1421818111166
Christof Koch141712105221
Andrew G. Clark140823123333
Stylianos E. Antonarakis13874693605
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202317
202270
2021836
2020810
2019854
2018764