Journal article
Order Under Uncertainty: Robust Differential Expression Analysis Using Probabilistic Models for Pseudotime Inference
- Abstract:
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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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(Version of record, pdf, 4.1MB)
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- Publisher copy:
- 10.1371/journal.pcbi.1005212
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Authors
Funding
+ John Fell Oxford University Press Research Fund
More from this funder
Funding agency for:
Yau, C
Grant:
090532/Z/09/Z
Bibliographic Details
- 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:
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1553-734X
- ISSN:
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1553-7358
Item Description
- Keywords:
- Pubs id:
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pubs:657014
- UUID:
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uuid:c4a234a8-309f-4012-8f8f-7f2d2dc4bd7f
- Local pid:
- pubs:657014
- Deposit date:
- 2016-11-03
Terms of use
- Copyright holder:
- © Campbell & Yau
- Copyright date:
- 2016
- Notes:
- © 2016 Campbell, Yau. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
- Licence:
- CC Attribution (CC BY)
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