RT Journal Article
SR Electronic
T1 An improved mode of running PASTA
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.08.30.274217
DO 10.1101/2020.08.30.274217
A1 Qikai Yang
A1 Tandy Warnow
YR 2020
UL http://biorxiv.org/content/early/2020/09/01/2020.08.30.274217.abstract
AB PASTA is a method for estimating alignments and trees that has been able to provide excellent accuracy on large sequence datasets. By design, PASTA operates using iteration, in which the tree from the previous iteration is used to inform a divide-and-conquer strategy during which a new alignment is computed on the sequence dataset, and then a new maximum likelihood tree is estimated on the new alignment. In its default setting, PASTA runs for three iterations and returns that alignment/tree pair from the last iteration. Here we use both biological and simulated nucleotide datasets to show that returning the alignment/tree pair that has the best maximum likelihood score improves on the default usage.Competing Interest StatementThe authors have declared no competing interest.