TreeShrink: fast and accurate detection of outlier long branches in collections of phylogenetic trees.

ABSTRACT:

Background

Sequence data used in reconstructing phylogenetic trees may include various sources of error. Typically errors are detected at the sequence level, but when missed, the erroneous sequences often appear as unexpectedly long branches in the inferred phylogeny.

Results

We propose an automatic method to detect such errors. We build a phylogeny including all the data then detect sequences that artificially inflate the tree diameter. We formulate an optimization problem, called the k-shrink problem, that seeks to find k leaves that could be removed to maximally reduce the tree diameter. We present an algorithm to find the exact solution for this problem in polynomial time. We then use several statistical tests to find outlier species that have an unexpectedly high impact

SUBMITTER: Mai U 

PROVIDER: S-EPMC5998883 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature