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Publication - Dr Tom Gaunt

    FATHMM-XF

    accurate prediction of pathogenic point mutations via extended features

    Citation

    Rogers, M, Shihab, HA, Mort, M, Cooper, DN, Gaunt, T & Campbell, C, 2017, ‘FATHMM-XF: accurate prediction of pathogenic point mutations via extended features’. Bioinformatics.

    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: 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.

    Full details in the University publications repository