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MutPred2: inferring the molecular and phenotypic impact of amino acid variants

Vikas Pejaver, Jorge Urresti, Jose Lugo-Martinez, Kymberleigh A. Pagel, Guan Ning Lin, Hyun-Jun Nam, Matthew Mort, David N. Cooper, Jonathan Sebat, Lilia M. Iakoucheva, Sean D. Mooney, Predrag Radivojac
doi: https://doi.org/10.1101/134981
Vikas Pejaver
1Indiana University, Bloomington, Indiana, U.S.A.
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Jorge Urresti
2University of California San Diego, La Jolla, California, U.S.A.
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Jose Lugo-Martinez
1Indiana University, Bloomington, Indiana, U.S.A.
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Kymberleigh A. Pagel
1Indiana University, Bloomington, Indiana, U.S.A.
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Guan Ning Lin
2University of California San Diego, La Jolla, California, U.S.A.
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Hyun-Jun Nam
2University of California San Diego, La Jolla, California, U.S.A.
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Matthew Mort
3Cardiff University, Cardiff, U.K.
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David N. Cooper
3Cardiff University, Cardiff, U.K.
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Jonathan Sebat
2University of California San Diego, La Jolla, California, U.S.A.
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Lilia M. Iakoucheva
2University of California San Diego, La Jolla, California, U.S.A.
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Sean D. Mooney
4University of Washington, Seattle, Washington, U.S.A.
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Predrag Radivojac
1Indiana University, Bloomington, Indiana, U.S.A.
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Abstract

We introduce MutPred2, a tool that improves the prioritization of pathogenic amino acid substitutions, generates molecular mechanisms potentially causative of disease, and returns interpretable pathogenicity score distributions on individual genomes. While its prioritization performance is state-of-the-art, a novel and distinguishing feature of MutPred2 is the probabilistic modeling of variant impact on specific aspects of protein structure and function that can serve to guide experimental studies of phenotype-altering variants. We demonstrate the utility of MutPred2 in the identification of the structural and functional mutational signatures relevant to Mendelian disorders and the prioritization of de novo mutations associated with complex neurodevelopmental disorders. We then experimentally validate the functional impact of several variants identified in patients with such disorders. We argue that mechanism-driven studies of human inherited diseases have the potential to significantly accelerate the discovery of clinically actionable variants.

Availability: http://mutpred.mutdb.org/

Footnotes

  • ↵* Contact: lilyak{at}ucsd.edu; sdmooney{at}uw.edu; predrag{at}indiana.edu

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted May 09, 2017.
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MutPred2: inferring the molecular and phenotypic impact of amino acid variants
Vikas Pejaver, Jorge Urresti, Jose Lugo-Martinez, Kymberleigh A. Pagel, Guan Ning Lin, Hyun-Jun Nam, Matthew Mort, David N. Cooper, Jonathan Sebat, Lilia M. Iakoucheva, Sean D. Mooney, Predrag Radivojac
bioRxiv 134981; doi: https://doi.org/10.1101/134981
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MutPred2: inferring the molecular and phenotypic impact of amino acid variants
Vikas Pejaver, Jorge Urresti, Jose Lugo-Martinez, Kymberleigh A. Pagel, Guan Ning Lin, Hyun-Jun Nam, Matthew Mort, David N. Cooper, Jonathan Sebat, Lilia M. Iakoucheva, Sean D. Mooney, Predrag Radivojac
bioRxiv 134981; doi: https://doi.org/10.1101/134981

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