AutoPhy: Automated phylogenetic identification of novel protein subfamilies.

ABSTRACT: Phylogenetic analysis of protein sequences provides a powerful means of identifying novel protein functions and subfamilies, and for identifying and resolving annotation errors. However, automation of functional clustering based on phylogenetic trees has been challenging and most of it is done manually. Clustering phylogenetic trees usually requires the delineation of tree-based thresholds (e.g., distances), leading to an ad hoc problem. We propose a new phylogenetic clustering approach that identifies clusters without using ad hoc distances or other pre-defined values. Our workflow combines uniform manifold approximation and projection (UMAP) with Gaussian mixture models as a k-means like procedure to automatically group sequences into clusters. We then apply a "second pass" clade identif

SUBMITTER: Ortiz-Velez AN 

PROVIDER: S-EPMC10783759 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature