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

ABSTRACT: 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.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/.mark.rogers@bristol.ac.uk or c.campbell@bristol.ac.uk.Supplementary data are available at Bioinformatics online.

SUBMITTER: Rogers MF

PROVIDER: S-EPMC5860356 | biostudies-other | 2018 Feb

REPOSITORIES: biostudies-other

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

Rogers Mark F MF Shihab Hashem A HA Mort Matthew M Cooper David N DN Gaunt Tom R TR Campbell Colin C

Bioinformatics (Oxford, England) 20180201 3

<h4>Summary</h4>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.<h4>Availability and implementation</h4>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. ...[more]

PMID: 28968714

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