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...
| Main Authors: | , , , |
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| Format: | Journal article |
| Language: | English |
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Public Library of Science
2016
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| _version_ | 1797087013065719808 |
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| author | O'Brien, J Iqbal, Z Wendler, J Amenga-Etego, L |
| author_facet | O'Brien, J Iqbal, Z Wendler, J Amenga-Etego, L |
| author_sort | O'Brien, J |
| collection | OXFORD |
| 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. |
| first_indexed | 2024-03-07T02:30:05Z |
| format | Journal article |
| id | oxford-uuid:a6f150f5-2d93-4a5a-b7a3-21bf4ae0760c |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T02:30:05Z |
| publishDate | 2016 |
| publisher | Public Library of Science |
| record_format | dspace |
| spelling | oxford-uuid:a6f150f5-2d93-4a5a-b7a3-21bf4ae0760c2022-03-27T02:51:02ZInferring strain mixture within clinical plasmodium falciparum isolates from genomic sequence dataJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:a6f150f5-2d93-4a5a-b7a3-21bf4ae0760cEnglishSymplectic Elements at OxfordPublic Library of Science2016O'Brien, JIqbal, ZWendler, JAmenga-Etego, LWe 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. |
| spellingShingle | O'Brien, J Iqbal, Z Wendler, J Amenga-Etego, L Inferring strain mixture within clinical plasmodium falciparum isolates from genomic sequence data |
| title | 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_short | 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 |
| work_keys_str_mv | AT obrienj inferringstrainmixturewithinclinicalplasmodiumfalciparumisolatesfromgenomicsequencedata AT iqbalz inferringstrainmixturewithinclinicalplasmodiumfalciparumisolatesfromgenomicsequencedata AT wendlerj inferringstrainmixturewithinclinicalplasmodiumfalciparumisolatesfromgenomicsequencedata AT amengaetegol inferringstrainmixturewithinclinicalplasmodiumfalciparumisolatesfromgenomicsequencedata |