Unknown

Dataset Information

VAAST 2.0: improved variant classification and disease-gene identification using a conservation-controlled amino acid substitution matrix.


ABSTRACT: The need for improved algorithmic support for variant prioritization and disease-gene identification in personal genomes data is widely acknowledged. We previously presented the Variant Annotation, Analysis, and Search Tool (VAAST), which employs an aggregative variant association test that combines both amino acid substitution (AAS) and allele frequencies. Here we describe and benchmark VAAST 2.0, which uses a novel conservation-controlled AAS matrix (CASM), to incorporate information about phylogenetic conservation. We show that the CASM approach improves VAAST's variant prioritization accuracy compared to its previous implementation, and compared to SIFT, PolyPhen-2, and MutationTaster. We also show that VAAST 2.0 outperforms KBAC, WSS, SKAT, and variable threshold (VT) using published

SUBMITTER: Hu H 

PROVIDER: S-EPMC3791556 | biostudies-literature | 2013 Sep

REPOSITORIES: biostudies-literature