Tools predicting the overal functional consequences of SNPs

This category collects together programs which evaluate the overall functional effects of SNPs. These programs commonly evaluate all the following things: intronic, 5'UTR, 3'UTR, 5-upstream. 3-downstream, splicing site and coding (synonymous or non-synonymous). So the basic concept is different from the programs listed in previous categories which usually focus only on one functional category of SNP effects. This category also contains tools which link SNP's to GO classes which may help in predicting the functional effect of SNPs. 

Programs available

• ANNOVAR
• SNPnexus
• FASTSNP
• Mutation@A Glance 
• Mutation assersor
• SNPtoGO
• SNP Effect Predictor + Ensembl Variation API

Description of programs

ANNOVAR



ANNOVA is an efficient software tool to utilize update-to-date information to functionally annotate genetic variants detected from diverse genomes. Given a list of variants with chromosome, start position, end position and observed nucleotides, ANNOVAR can identify whether SNPs or indels cause protein coding changes and what is the amino acids that were changed, or identify variants in conserved genomic regions, or identify variants that are reported in dbSNP, or identify the subset of common SNPs (MAF>1%) in the 1000 Genome Project, or identify subset of non-synonymous SNPs with SIFT score>0.05...

In a modern desktop computer (3GHz Intel Xeon CPU, 8Gb memory), for 4.7 million variants, ANNOVAR requires ~4 minutes to perform gene-based functional annotation, or ~15 minutes to perform stepwise "variants reduction" procedure, making it practical to handle hundreds of human genomes in a day.

website: ANNOVAR

Download: here

Reference: Wang et al. ANNOVAR: Functional annotation of genetic variants from next-generation sequencing data Nucleic Acids Research, doi:10.1093/nar/gkq603, 2010 

SNPnexus

SNPnexus is a tool which allows the functional annotation of newly discovered and public SNPs.  It raports the possible effects on the transciptome and proteome levels. The following analysis are available for SNPS:  computationally predicted functional SNP consequences of SNPs in  intronic, 5'UTR, 3'UTR, 5-upstram, 3-downstream, splicing site or coding (synonumous or non-synonymous) categories, links to dbSNP and HapMap data, analysis of regulatory SNPs, links to published scientific papers and overlaps of putative copy number polymorphisms (CNP).  As an input SNPnexus takes either area and the position of the SNP (for novel SNPs) or the dbSNP id.

website: SNPnexus

Download:

Reference: Chelala et al. SNPnexus: A web database for functional annotation of newly discovered and public domain Single Nucleotide Polymorphisms, Bioinformatics, 2009, 25(5):655-61. doi:10.1093/bioinformatics/btn653

FASTSNP

FASTSNP provides SNP prioritization services based on the information collected from the Internet at query time. FASTSNP's priorization results is based on the predicted functional effects and their estimated risk proposed by Tabor et al.  SNPs are prioritized according to twelve phenotypic  risks and putative functional effects. For example the following things are taken into account as potential functional effects: the premature translation termination (nonsense; stop codon gained), the exons that cause an amino acid change (non-synonymous), the splicing sites, the transcription factor binding sites at promoter regions,the exonic splicing enhancer motifs,the exonic splicing silencer motifs and the 3utr post-transcriptional regulatory region. As an input FASTSNP requires either name of the gene,  SNP list or novel SNP sequence. As an output you get a SNP Function Report for each SNP.

website: FASTSNP

Download:

Reference:Yuan et al. FASTSNP: an always up-to-date and extendable service for SNP function analysis and prioritization. Nucleic Acids Res., 2006, 34, Web Server issue, W635-41. doi:10.1093/nar/gkl236

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Mutation @ A Glance

Mutation@A Glance locates already known genetic variation data individually on the nucleotide and the amino acid sequences and makes it possible to cross-reference them with tertiary and/or quaternary protein structures and various functional features associated with specific amino acid residues in the proteins.

website: Mutation@A Glance

Reference: Hijikata A., et al. Mutation@A Glance: An integrative web application for analysing mutations from human genetic diseases. DNA Res. 2010. doi: 10.1093/dnares/dsq010

Mutation assersor

The server predicts the functional impact of amino-acid substitutions in proteins, such as mutations discovered in cancer or nonsynonymous polymorphisms. The functional impact is assessed based on evolutionary conservation of the affected amino acid in protein homologs.

website: http://mutationassessor.org/

SNPtoGO

SNPtoGO is a web based tool  which can be used to connect SNPs to GO classes. This can be useful because while studying complex polygenic diseases patients are not expected to have identical sets of genes. However one expects overlaps in the sets of genes that  are involved in the same molecular processes. 

website: SNPtoGO

Download: here

Reference: Schwarz et al. SNPtoGO: characterizing SNPs by enriched GO terms. Bioinformatics 2008 24(1):146-148; doi:10.1093/bioinformatics/btm551. 

SNP Effect Predictor + Ensembl Variation API

SNP Effect Predictor which can be used through API interface or as web-based tool can functionally annotate variants in all Ensembl and Ensembl Genomes supported species.  Consequence types provide information about to which transcript section the allele affects and in which way (consequence types by SNP Effect Predictor)

web-based tool:

website: SNP Effect Predictor (select the SNP Effect Predictor)

Download: here

Reference: McLaren W, Pritchard B, Rios D, Chen Y, Flicek P, Cunningham F Deriving the consequences of genomic variants with the Ensembl API and SNP Effect Predictor. Bioinformatics. 2010 Aug 15;26(16):2069-70. Epub 2010 Jun 18.doi: 10.1093/bioinformatics/btq330

Ensembl Variation API:

* Main page

* documentation

Reference: Chen et al. Ensembl variation resources. BMC Genomics 11(1):293 (2010). doi:10.1186/1471-2164-11-293

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Useful databases

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Review articles

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Other articles

• Tabor et al. (2002) Opinion: candidate-gene approaches for studying complex genetic traits: practical considerations Nature Rev. Genet, . 3, 391–397. doi: 10.1038/nrg796

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Useful Links

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