Inferring Strain Mixture within Clinical Plasmodium falciparum Isolates from Genomic Sequence Data

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 mi...

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Main Authors:	O’Brien, John D., Iqbal, Zamin, Wendler, Jason, Amenga-Etego, Lucas
Format:	Online
Language:	English
Published:	Public Library of Science 2016
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4928962/

id	pubmed-4928962
recordtype	oai_dc
spelling	pubmed-49289622016-07-18 Inferring Strain Mixture within Clinical Plasmodium falciparum Isolates from Genomic Sequence Data O’Brien, John D. Iqbal, Zamin Wendler, Jason Amenga-Etego, Lucas Research Article 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 model are provided in an open source fashion. We discuss the possible uses of this model as a window into within-host selection for clinical and epidemiological studies. Public Library of Science 2016-06-30 /pmc/articles/PMC4928962/ /pubmed/27362949 http://dx.doi.org/10.1371/journal.pcbi.1004824 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	O’Brien, John D. Iqbal, Zamin Wendler, Jason Amenga-Etego, Lucas
spellingShingle	O’Brien, John D. Iqbal, Zamin Wendler, Jason Amenga-Etego, Lucas Inferring Strain Mixture within Clinical Plasmodium falciparum Isolates from Genomic Sequence Data
author_facet	O’Brien, John D. Iqbal, Zamin Wendler, Jason Amenga-Etego, Lucas
author_sort	O’Brien, John D.
title	Inferring Strain Mixture within Clinical Plasmodium falciparum Isolates from Genomic Sequence Data
title_short	Inferring Strain Mixture within Clinical Plasmodium falciparum Isolates from Genomic Sequence Data
title_full	Inferring Strain Mixture within Clinical Plasmodium falciparum Isolates from Genomic Sequence Data
title_fullStr	Inferring Strain Mixture within Clinical Plasmodium falciparum Isolates from Genomic Sequence Data
title_full_unstemmed	Inferring Strain Mixture within Clinical Plasmodium falciparum Isolates from Genomic Sequence Data
title_sort	inferring strain mixture within clinical plasmodium falciparum isolates from genomic sequence data
description	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 model are provided in an open source fashion. We discuss the possible uses of this model as a window into within-host selection for clinical and epidemiological studies.
publisher	Public Library of Science
publishDate	2016
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4928962/
_version_	1613602635132174336

Inferring Strain Mixture within Clinical Plasmodium falciparum Isolates from Genomic Sequence Data

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