APPLES: Scalable Distance-Based Phylogenetic Placement with or without Alignments.

ABSTRACT: Placing a new species on an existing phylogeny has increasing relevance to several applications. Placement can be used to update phylogenies in a scalable fashion and can help identify unknown query samples using (meta-)barcoding, skimming, or metagenomic data. Maximum likelihood (ML) methods of phylogenetic placement exist, but these methods are not scalable to reference trees with many thousands of leaves, limiting their ability to enjoy benefits of dense taxon sampling in modern reference libraries. They also rely on assembled sequences for the reference set and aligned sequences for the query. Thus, ML methods cannot analyze data sets where the reference consists of unassembled reads, a scenario relevant to emerging applications of genome skimming for sample identification. We introduc

SUBMITTER: Balaban M 

PROVIDER: S-EPMC7164367 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature