K-Pax2: Bayesian identification of cluster-defining amino acid positions in large sequence datasets.

ABSTRACT: The recent growth in publicly available sequence data has introduced new opportunities for studying microbial evolution and spread. Because the pace of sequence accumulation tends to exceed the pace of experimental studies of protein function and the roles of individual amino acids, statistical tools to identify meaningful patterns in protein diversity are essential. Large sequence alignments from fast-evolving micro-organisms are particularly challenging to dissect using standard tools from phylogenetics and multivariate statistics because biologically relevant functional signals are easily masked by neutral variation and noise. To meet this need, a novel computational method is introduced that is easily executed in parallel using a cluster environment and can handle thousands of sequence

SUBMITTER: Pessia A 

PROVIDER: S-EPMC5320600 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature