FATHMM-XF: accurate prediction of pathogenic point mutations via extended features
Bioinformatics, 2018•academic.oup.com
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 …
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 …
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.
Oxford University Press