Comparison and integration of deleteriousness prediction methods for nonsynonymous SNVs in whole exome sequencing studies
NeuroGenetic Pharmaceuticals (United States) · Center for Human Genetics · +5 more institutions
Abstract
Accurate deleteriousness prediction for nonsynonymous variants is crucial for distinguishing pathogenic mutations from background polymorphisms in whole exome sequencing (WES) studies. Although many deleteriousness prediction methods have been developed, their prediction results are sometimes inconsistent with each other and their relative merits are still unclear in practical applications. To address these issues, we comprehensively evaluated the predictive performance of 18 current deleteriousness-scoring methods, including 11 function prediction scores (PolyPhen-2, SIFT, MutationTaster, Mutation Assessor, FATHMM, LRT, PANTHER, PhD-SNP, SNAP, SNPs&GO and MutPred), 3 conservation scores (GERP++, SiPhy and…
Citation impact
- FWCI
- 37.44
- Percentile
- 100%
- References
- 50
Authors
7- CDCaixia DongCorresponding
NeuroGenetic Pharmaceuticals (United States)
- PWPeng Wei
Center for Human Genetics, The University of Texas Health Science Center at Houston
- XJX. Jian
- RARichard A. Gibbs
Baylor College of Medicine
- EBEric Boerwinkle
Baylor College of Medicine, Center for Human Genetics, Baylor Genetics
Topics & keywords
- Nonsynonymous substitution
- Discriminative model
- Exome
- Exome sequencing
- Biology
- Artificial intelligence
- Machine learning
- SNP
- Reduced inequalities