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Inferring strain mixture within clinical plasmodium falciparum isolates from genomic sequence data

Abstract:

We present a rigorous statistical model that infers the structure of P. falciparum mixtures-including the number of strains present, their proportion within the samples, and the amount of unexplained mixture-using whole genome sequence (WGS) data. Applied to simulation data, artificial laboratory mixtures, and field samples, the model provides reasonable inference with as few as 10 reads or 50 SNPs and works efficiently even with much larger data sets. Source code and example data for the mod...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Publisher's version

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Publisher copy:
10.1371/journal.pcbi.1004824

Authors


O'Brien, JD More by this author
More by this author
Institution:
University of Oxford
Department:
Oxford, MSD, NDM, Human Genetics Wt Centre
Wendler, J More by this author
Amenga-Etego, L More by this author
Publisher:
Public Library of Science Publisher's website
Journal:
PLoS Computational Biology Journal website
Volume:
12
Issue:
6
Pages:
e1004824
Publication date:
2016-06-30
Acceptance date:
2016-02-17
DOI:
EISSN:
1553-7358
ISSN:
1553-734X
URN:
pubs:a6f150f5-2d93-4a5a-b7a3-21bf4ae0760c
Source identifiers:
634290
Local pid:
info:fedora/pubs:634290
Language:
English
Keywords:

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