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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: The aim of this article is to review the potential applications of NGS in paediatrics and to assess the need for further research into this area.
Abstract: Next generation sequencing (NGS), massively parallel or deep sequencing are related terms that describe a DNA sequencing technology which has revolutionised genomic research. Using NGS an entire human genome can be sequenced within a single day. In contrast, the previous Sanger sequencing technology, used to decipher the human genome, required over a decade to deliver the final draft. Although in genome research NGS has mostly superseded conventional Sanger sequencing, it has not yet translated into routine clinical practice. The aim of this article is to review the potential applications of NGS in paediatrics.

456 citations

Journal ArticleDOI
26 Sep 2013-Cell
TL;DR: Using the FUCCI reporter system in human pluripotent stem cells is used to demonstrate that cell fate decisions are tightly associated with the cell-cycle machinery and reveal insights in the mechanisms synchronizing differentiation and proliferation in developing tissues.

455 citations

Journal ArticleDOI
TL;DR: WormBase ParaSite (http://parasite.wormbase.org) as mentioned in this paper is a portal for the analysis of helminth genomic data, including worms and platy helminths.

455 citations

Journal ArticleDOI
14 Mar 2013-Cell
TL;DR: Conceptual criteria for the inference of chromothripsis is described, based on ruling out the alternative hypothesis that stepwise rearrangements occurred, and it is suggested that robust means of inference may facilitate in-depth studies on the impact of, and the mechanisms underlying, chromothRIpsis.

453 citations

Journal ArticleDOI
TL;DR: BCFtools/RoH is presented and evaluated, an extension to the BCFtools software package, that detects regions of autozygosity in sequencing data, in particular exome data, using a hidden Markov model and it is shown that it has higher sensitivity and specificity than existing methods under a range of sequencing error rates and levels of autozykgosity.
Abstract: Summary: Runs of homozygosity (RoHs) are genomic stretches of a diploid genome that show identical alleles on both chromosomes. Longer RoHs are unlikely to have arisen by chance but are likely to denote autozygosity, whereby both copies of the genome descend from the same recent ancestor. Early tools to detect RoH used genotype array data, but substantially more information is available from sequencing data. Here, we present and evaluate BCFtools/RoH, an extension to the BCFtools software package, that detects regions of autozygosity in sequencing data, in particular exome data, using a hidden Markov model. By applying it to simulated data and real data from the 1000 Genomes Project we estimate its accuracy and show that it has higher sensitivity and specificity than existing methods under a range of sequencing error rates and levels of autozygosity. Availability and implementation: BCFtools/RoH and its associated binary/source files are freely available from https://github.com/samtools/BCFtools. Contact: ku.ca.regnas@2nv or ku.ca.regnas@3dp Supplementary information: Supplementary data are available at Bioinformatics online.

452 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