Microbial community dissimilarity for source tracking with application in forensic studies.
Microbial source-tracking is a useful tool for trace evidence analysis in Forensics. Community-wide massively parallel sequencing profiles can bypass the need for satellite microbes or marker sets, which are unreliable when handling unstable samples. We propose a novel method utilizing Aitchison dis...
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doaj-66a92954f4d4421a9bf9ff8c705cc1472021-03-03T21:57:35ZengPublic Library of Science (PLoS)PLoS ONE1932-62032020-01-01157e023608210.1371/journal.pone.0236082Microbial community dissimilarity for source tracking with application in forensic studies.Kyle M CarterMeng LuQianwen LuoHongmei JiangLingling AnMicrobial source-tracking is a useful tool for trace evidence analysis in Forensics. Community-wide massively parallel sequencing profiles can bypass the need for satellite microbes or marker sets, which are unreliable when handling unstable samples. We propose a novel method utilizing Aitchison distance to select important suspects/sources, and then integrate it with existing algorithms in source tracking to estimate the proportions of microbial sample coming from important suspects/sources. A series of comprehensive simulation studies show that the proposed method is capable of accurate selection and therefore improves the performance of current methods such as Bayesian SourceTracker and FEAST in the presence of noise microbial sources.https://doi.org/10.1371/journal.pone.0236082 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Kyle M Carter Meng Lu Qianwen Luo Hongmei Jiang Lingling An |
spellingShingle |
Kyle M Carter Meng Lu Qianwen Luo Hongmei Jiang Lingling An Microbial community dissimilarity for source tracking with application in forensic studies. PLoS ONE |
author_facet |
Kyle M Carter Meng Lu Qianwen Luo Hongmei Jiang Lingling An |
author_sort |
Kyle M Carter |
title |
Microbial community dissimilarity for source tracking with application in forensic studies. |
title_short |
Microbial community dissimilarity for source tracking with application in forensic studies. |
title_full |
Microbial community dissimilarity for source tracking with application in forensic studies. |
title_fullStr |
Microbial community dissimilarity for source tracking with application in forensic studies. |
title_full_unstemmed |
Microbial community dissimilarity for source tracking with application in forensic studies. |
title_sort |
microbial community dissimilarity for source tracking with application in forensic studies. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2020-01-01 |
description |
Microbial source-tracking is a useful tool for trace evidence analysis in Forensics. Community-wide massively parallel sequencing profiles can bypass the need for satellite microbes or marker sets, which are unreliable when handling unstable samples. We propose a novel method utilizing Aitchison distance to select important suspects/sources, and then integrate it with existing algorithms in source tracking to estimate the proportions of microbial sample coming from important suspects/sources. A series of comprehensive simulation studies show that the proposed method is capable of accurate selection and therefore improves the performance of current methods such as Bayesian SourceTracker and FEAST in the presence of noise microbial sources. |
url |
https://doi.org/10.1371/journal.pone.0236082 |
work_keys_str_mv |
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