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

Research output: Contribution to journalArticle

Original languageEnglish
Article numberbtx536
Number of pages3
JournalBioinformatics
Early online date5 Sep 2017
DOIs
StateE-pub ahead of print - 5 Sep 2017

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.

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    Rights statement: This is the final published version of the article (version of record). It first appeared online via Oxford University Press at https://academic.oup.com/bioinformatics/article/doi/10.1093/bioinformatics/btx536/4104409/FATHMMXF-accurate-prediction-of-pathogenic-point. Please refer to any applicable terms of use of the publisher.

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    License: CC BY

  • Supplementary information PDF

    Rights statement: This is the final published version of the article (version of record). It first appeared online via Oxford University Press at https://academic.oup.com/bioinformatics/article/doi/10.1093/bioinformatics/btx536/4104409/FATHMMXF-accurate-prediction-of-pathogenic-point. Please refer to any applicable terms of use of the publisher.

    Final published version, 643 KB, PDF-document

    License: CC BY

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