Using bioinformatics to predict the functional impact of SNVs
Open Access
- 14 December 2010
- journal article
- review article
- Published by Oxford University Press (OUP) in Bioinformatics
- Vol. 27 (4), 441-448
- https://doi.org/10.1093/bioinformatics/btq695
Abstract
Motivation: The past decade has seen the introduction of fast and relatively inexpensive methods to detect genetic variation across the genome and exponential growth in the number of known single nucleotide variants (SNVs). There is increasing interest in bioinformatics approaches to identify variants that are functionally important from millions of candidate variants. Here, we describe the essential components of bionformatics tools that predict functional SNVs. Results: Bioinformatics tools have great potential to identify functional SNVs, but the black box nature of many tools can be a pitfall for researchers. Understanding the underlying methods, assumptions and biases of these tools is essential to their intelligent application. Contact:karchin@jhu.edu Supplementary information: Supplementary data are available at Bioinformatics online.Keywords
This publication has 73 references indexed in Scilit:
- A map of human genome variation from population-scale sequencingNature, 2010
- Discovery and characterization of chromatin states for systematic annotation of the human genomeNature Biotechnology, 2010
- Genetic Heterogeneity in Human DiseaseCell, 2010
- Prioritizing GWAS Results: A Review of Statistical Methods and Recommendations for Their ApplicationAmerican Journal of Human Genetics, 2010
- The diploid genome sequence of an Asian individualNature, 2008
- The complete genome of an individual by massively parallel DNA sequencingNature, 2008
- Conserved Seed Pairing, Often Flanked by Adenosines, Indicates that Thousands of Human Genes are MicroRNA TargetsCell, 2005
- Prediction of post‐translational glycosylation and phosphorylation of proteins from the amino acid sequenceProteomics, 2004
- The Swiss-Prot variant page and the ModSNP database: A resource for sequence and structure information on human protein variantsHuman Mutation, 2004
- The International HapMap ProjectNature, 2003