A general species delimitation method with applications to phylogenetic placements
Author(s) -
Jiajie Zhang,
Paschalia Kapli,
Pavlos Pavlidis,
Alexandros Stamatakis
Publication year - 2013
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btt499
Subject(s) - coalescent theory , phylogenetic tree , markov chain monte carlo , computer science , bayesian probability , tree (set theory) , biology , computational biology , artificial intelligence , mathematics , genetics , mathematical analysis , gene
Sequence-based methods to delimit species are central to DNA taxonomy, microbial community surveys and DNA metabarcoding studies. Current approaches either rely on simple sequence similarity thresholds (OTU-picking) or on complex and compute-intensive evolutionary models. The OTU-picking methods scale well on large datasets, but the results are highly sensitive to the similarity threshold. Coalescent-based species delimitation approaches often rely on Bayesian statistics and Markov Chain Monte Carlo sampling, and can therefore only be applied to small datasets.
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