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

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 fou...

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Vydané v:Bioinformatics Ročník 34; číslo 3; s. 511 - 513
Hlavní autori: Rogers, Mark F, Shihab, Hashem A, Mort, Matthew, Cooper, David N, Gaunt, Tom R, Campbell, Colin
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: England Oxford University Press 01.02.2018
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Applications Notes
Genome, Human
Genomics - methods
Humans
Point Mutation
Sequence Analysis, DNA - methods
Software
ISSN:1367-4803, 1367-4811, 1460-2059, 1367-4811
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Shrnutí: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/ Supplementary information Supplementary data are available at Bioinformatics online.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
Tom R. Gaunt and Colin Campbell authors wish it to be known that, in their opinion, the last two authors should be regarded as Joint Last Authors.
ISSN:1367-4803
1367-4811
1460-2059
1367-4811
DOI:10.1093/bioinformatics/btx536