Format

Send to

Choose Destination
PLoS Comput Biol. 2017 Jun 22;13(6):e1005628. doi: 10.1371/journal.pcbi.1005628. eCollection 2017 Jun.

High-confidence assessment of functional impact of human mitochondrial non-synonymous genome variations by APOGEE.

Author information

1
IRCCS Casa Sollievo della Sofferenza, Bioinformatics unit, San Giovanni Rotondo (FG), Italy.
2
IRCCS Casa Sollievo della Sofferenza, Department of Medical Sciences, Division of Internal Medicine, San Giovanni Rotondo (FG), Italy.
3
IRCCS Casa Sollievo della Sofferenza, Medical Genetics unit, San Giovanni Rotondo (FG), Italy.
4
IRCSS Casa Sollievo della Sofferenza, ISBReMIT- Institute for Stem Cell Biology, Regenerative Medicine and Innovative Therapies, San Giovanni Rotondo (FG), Italy.
5
University of Milano Bicocca, Department of Biotechnology and Biosciences, Milan, Italy.

Abstract

24,189 are all the possible non-synonymous amino acid changes potentially affecting the human mitochondrial DNA. Only a tiny subset was functionally evaluated with certainty so far, while the pathogenicity of the vast majority was only assessed in-silico by software predictors. Since these tools proved to be rather incongruent, we have designed and implemented APOGEE, a machine-learning algorithm that outperforms all existing prediction methods in estimating the harmfulness of mitochondrial non-synonymous genome variations. We provide a detailed description of the underlying algorithm, of the selected and manually curated training and test sets of variants, as well as of its classification ability.

PMID:
28640805
PMCID:
PMC5501658
DOI:
10.1371/journal.pcbi.1005628
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Public Library of Science Icon for PubMed Central
Loading ...
Support Center