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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: DeepCpG, a computational approach based on deep neural networks to predict methylation states in single cells, yields substantially more accurate predictions than previous methods and can be interpreted, thereby providing insights into how sequence composition affects methylation variability.
Abstract: Recent technological advances have enabled DNA methylation to be assayed at single-cell resolution. However, current protocols are limited by incomplete CpG coverage and hence methods to predict missing methylation states are critical to enable genome-wide analyses. We report DeepCpG, a computational approach based on deep neural networks to predict methylation states in single cells. We evaluate DeepCpG on single-cell methylation data from five cell types generated using alternative sequencing protocols. DeepCpG yields substantially more accurate predictions than previous methods. Additionally, we show that the model parameters can be interpreted, thereby providing insights into how sequence composition affects methylation variability.

388 citations

Journal ArticleDOI
06 Oct 2017-Science
TL;DR: An overview of the state of single-cell genomics methods and an outlook on the use ofsingle-cell techniques to decipher the adaptive and innate components of immunity are provided.
Abstract: The immune system varies in cell types, states, and locations. The complex networks, interactions, and responses of immune cells produce diverse cellular ecosystems composed of multiple cell types, accompanied by genetic diversity in antigen receptors. Within this ecosystem, innate and adaptive immune cells maintain and protect tissue function, integrity, and homeostasis upon changes in functional demands and diverse insults. Characterizing this inherent complexity requires studies at single-cell resolution. Recent advances such as massively parallel single-cell RNA sequencing and sophisticated computational methods are catalyzing a revolution in our understanding of immunology. Here we provide an overview of the state of single-cell genomics methods and an outlook on the use of single-cell techniques to decipher the adaptive and innate components of immunity.

388 citations

Journal ArticleDOI
TL;DR: In this article, the authors found a genome-wide significant association between rare loss-of-function (LoF) variants in SETD1A and risk for schizophrenia (P = 3.3 × 10−9).
Abstract: By analyzing the whole-exome sequences of 4,264 schizophrenia cases, 9,343 controls and 1,077 trios, we identified a genome-wide significant association between rare loss-of-function (LoF) variants in SETD1A and risk for schizophrenia (P = 3.3 × 10−9). We found only two heterozygous LoF variants in 45,376 exomes from individuals without a neuropsychiatric diagnosis, indicating that SETD1A is substantially depleted of LoF variants in the general population. Seven of the ten individuals with schizophrenia carrying SETD1A LoF variants also had learning difficulties. We further identified four SETD1A LoF carriers among 4,281 children with severe developmental disorders and two more carriers in an independent sample of 5,720 Finnish exomes, both with notable neuropsychiatric phenotypes. Together, our observations indicate that LoF variants in SETD1A cause a range of neurodevelopmental disorders, including schizophrenia. Combining these data with previous common variant evidence, we suggest that epigenetic dysregulation, specifically in the histone H3K4 methylation pathway, is an important mechanism in the pathogenesis of schizophrenia.

388 citations

Journal ArticleDOI
TL;DR: An unbiased sorting strategy is designed that separates non-HSCs away from HSCs, and single-cell transplantation experiments using the enriched population were combined with RNA-seq data to identify key molecules that associate with long-term durable self-renewal, producing a single- cell molecular dataset that is linked to functional stem cell activity.

387 citations

Journal ArticleDOI
TL;DR: It is shown that whole-genome sequence data reveals genetic structure within these lines not shown by multilocus typing, and suggests that drug resistance has emerged multiple times in this closely related set of lines, providing additional power to track the drug resistance and epidemiology of an important human pathogen.
Abstract: Visceral leishmaniasis is a potentially fatal disease endemic to large parts of Asia and Africa, primarily caused by the protozoan parasite Leishmania donovani. Here, we report a high-quality reference genome sequence for a strain of L. donovani from Nepal, and use this sequence to study variation in a set of 16 related clinical lines, isolated from visceral leishmaniasis patients from the same region, which also differ in their response to in vitro drug susceptibility. We show that whole-genome sequence data reveals genetic structure within these lines not shown by multilocus typing, and suggests that drug resistance has emerged multiple times in this closely related set of lines. Sequence comparisons with other Leishmania species and analysis of single-nucleotide diversity within our sample showed evidence of selection acting in a range of surface- and transport-related genes, including genes associated with drug resistance. Against a background of relative genetic homogeneity, we found extensive variation in chromosome copy number between our lines. Other forms of structural variation were significantly associated with drug resistance, notably including gene dosage and the copy number of an experimentally verified circular episome present in all lines and described here for the first time. This study provides a basis for more powerful molecular profiling of visceral leishmaniasis, providing additional power to track the drug resistance and epidemiology of an important human pathogen.

387 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