Journal
BIOINFORMATICS
Volume 34, Issue 3, Pages 511-513Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btx536
Keywords
-
Categories
Funding
- Engineering and Physical Sciences Research Council (EPSRC) [EP/M01715X/1, EP/K008250/1]
- Medical Research Council Integrative Epidemiology Unit (MRC IEU) [MC UU 12013/8]
- Qiagen Inc.
- Cardiff University
- EPSRC [EP/K008250/1, EP/M01715X/1] Funding Source: UKRI
- MRC [G1000427, MC_UU_12013/8, MC_UU_00011/4] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [EP/K008250/1, EP/M01715X/1] Funding Source: researchfish
- Medical Research Council [MC_UU_00011/4, G1000427, MC_UU_12013/8] Funding Source: researchfish
Ask authors/readers for more resources
aSummary: 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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available