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pcaReduce: Hierarchical clustering of single cell transcriptional profiles

Abstract:
Background: Advances in single cell genomics provide a way of routinely generating transcriptomics data at the single cell level. A frequent requirement of single cell expression analysis is the identification of novel patterns of heterogeneity across single cells that might explain complex cellular states or tissue composition. To date, classical statistical analysis tools have being routinely applied, but there is considerable scope for the development of novel statistical ... Expand abstract
Publication status:
Published
Peer review status:
Peer reviewed
Version:
Publisher's version

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Publisher copy:
10.1186/s12859-016-0984-y

Authors


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Institution:
University of Oxford
Department:
Oxford, MSD, NDM, Human Genetics Wt Centre
Role:
Author
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Institution:
University of Oxford
Department:
Oxford, MSD, NDM, Human Genetics Wt Centre
Role:
Author
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Grant:
Core Award 090532/Z/09/Z
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Grant:
Oxford-Stanford Big Data for Human Health Seed Grant
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Grant:
New Investigator Research Grant (MR/L001411/1)
Publisher:
BioMed Central Publisher's website
Journal:
BMC Bioinformatics Journal website
Volume:
17
Pages:
Article: 140
Publication date:
2016-01-01
DOI:
ISSN:
1471-2105
URN:
uuid:aa2748ea-2a94-48f0-82dc-4babeb532f66
Source identifiers:
610656
Local pid:
pubs:610656

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