FATHMM-XF: accurate prediction of pathogenic point mutations via extended features

Abstract Summary We present FATHMM-XF, a method for predicting pathogenic point mutations in the human genome. Drawing on an extensive feature set, FATHMM-XF outperforms competitors on benchmark tests, particularly in non-coding regions where the majority of pathogenic mutations are likely to be fou...

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Bibliographic Details
Published inBioinformatics Vol. 34; no. 3; pp. 511 - 513
Main Authors Rogers, Mark F, Shihab, Hashem A, Mort, Matthew, Cooper, David N, Gaunt, Tom R, Campbell, Colin
Format Journal Article
LanguageEnglish
Published England Oxford University Press 01.02.2018
Subjects
Applications Notes
Genome, Human
Genomics - methods
Humans
Point Mutation
Sequence Analysis, DNA - methods
Software
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Summary:Abstract Summary We present FATHMM-XF, a method for predicting pathogenic point mutations in the human genome. Drawing on an extensive feature set, FATHMM-XF outperforms competitors on benchmark tests, particularly in non-coding regions where the majority of pathogenic mutations are likely to be found. Availability and implementation The FATHMM-XF web server is available at http://fathmm.biocompute.org.uk/fathmm-xf/, and as tracks on the Genome Tolerance Browser: http://gtb.biocompute.org.uk. Predictions are provided for human genome version GRCh37/hg19. The data used for this project can be downloaded from: http://fathmm.biocompute.org.uk/fathmm-xf/ Supplementary information Supplementary data are available at Bioinformatics online.
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Tom R. Gaunt and Colin Campbell authors wish it to be known that, in their opinion, the last two authors should be regarded as Joint Last Authors.
ISSN:1367-4803
1367-4811
1460-2059
1367-4811
DOI:10.1093/bioinformatics/btx536