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Bioinformatics. 2016 Jul 15;32(14):2230-2. doi: 10.1093/bioinformatics/btw222. Epub 2016 May 18.

PANTHER-PSEP: predicting disease-causing genetic variants using position-specific evolutionary preservation.

Author information

1
Division of Bioinformatics, Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90033, USA.

Abstract

PANTHER-PSEP is a new software tool for predicting non-synonymous genetic variants that may play a causal role in human disease. Several previous variant pathogenicity prediction methods have been proposed that quantify evolutionary conservation among homologous proteins from different organisms. PANTHER-PSEP employs a related but distinct metric based on 'evolutionary preservation': homologous proteins are used to reconstruct the likely sequences of ancestral proteins at nodes in a phylogenetic tree, and the history of each amino acid can be traced back in time from its current state to estimate how long that state has been preserved in its ancestors. Here, we describe the PSEP tool, and assess its performance on standard benchmarks for distinguishing disease-associated from neutral variation in humans. On these benchmarks, PSEP outperforms not only previous tools that utilize evolutionary conservation, but also several highly used tools that include multiple other sources of information as well. For predicting pathogenic human variants, the trace back of course starts with a human 'reference' protein sequence, but the PSEP tool can also be applied to predicting deleterious or pathogenic variants in reference proteins from any of the ∼100 other species in the PANTHER database.

AVAILABILITY AND IMPLEMENTATION:

PANTHER-PSEP is freely available on the web at http://pantherdb.org/tools/csnpScoreForm.jsp Users can also download the command-line based tool at ftp://ftp.pantherdb.org/cSNP_analysis/PSEP/ CONTACT: pdthomas@usc.edu

SUPPLEMENTARY INFORMATION:

Supplementary data are available at Bioinformatics online.

PMID:
27193693
DOI:
10.1093/bioinformatics/btw222
[Indexed for MEDLINE]

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