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Order Under Uncertainty: Robust Differential Expression Analysis Using Probabilistic Models for Pseudotime Inference

Abstract:

Single cell gene expression profiling can be used to quantify transcriptional dynamics in temporal processes, such as cell differentiation, using computational methods to label each cell with a ‘pseudotime’ where true time series experimentation is too difficult to perform. However, owing to the high variability in gene expression between individual cells, there is an inherent uncertainty in the precise temporal ordering of the cells. Preexisting methods for pseudotime estimation have predomi...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1371/journal.pcbi.1005212

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Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Human Genetics Wt Centre
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Human Genetics Wt Centre
Role:
Author
More from this funder
Funding agency for:
Campbell, K
More from this funder
Funding agency for:
Yau, C
Grant:
090532/Z/09/Z
More from this funder
Funding agency for:
Yau, C
Grant:
090532/Z/09/Z
More from this funder
Funding agency for:
Yau, C
Grant:
090532/Z/09/Z
More from this funder
Funding agency for:
Yau, C
Grant:
090532/Z/09/Z
Publisher:
Public Library of Science Publisher's website
Journal:
PLoS Computational Biology Journal website
Volume:
12
Issue:
11
Pages:
e1005212
Publication date:
2016-11-21
Acceptance date:
2016-10-13
DOI:
EISSN:
1553-734X
ISSN:
1553-7358
Keywords:
Pubs id:
pubs:657014
UUID:
uuid:c4a234a8-309f-4012-8f8f-7f2d2dc4bd7f
Local pid:
pubs:657014
Deposit date:
2016-11-03

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