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

Bioinformatics. 2018 Feb 1;34(3):511-513. doi: 10.1093/bioinformatics/btx536.

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/.

Contact: mark.rogers@bristol.ac.uk or c.campbell@bristol.ac.uk.

Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Genome, Human
  • Genomics / methods*
  • Humans
  • Point Mutation*
  • Sequence Analysis, DNA / methods*
  • Software*