Large multiple sequence alignments with a root-to-leaf regressive method.

ABSTRACT: Multiple sequence alignments (MSAs) are used for structural^1,2 and evolutionary predictions^1,2, but the complexity of aligning large datasets requires the use of approximate solutions³, including the progressive algorithm⁴. Progressive MSA methods start by aligning the most similar sequences and subsequently incorporate the remaining sequences, from leaf to root, based on a guide tree. Their accuracy declines substantially as the number of sequences is scaled up⁵. We introduce a regressive algorithm that enables MSA of up to 1.4 million sequences on a standard workstation and substantially improves accuracy on datasets larger than 10,000 sequences. Our regressive algorithm works the other way around from the progressive algorithm and b

SUBMITTER: Garriga E 

PROVIDER: S-EPMC6894943 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature