Prediction tools

Tools predicting protein level changes and disease susceptibility

These tools have been extensively covered in the review written by Janita Thusberg and Mauno Vihinen and many of them can be found from the PON-P tool.

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Meta tools

Meta tools are tools that use two or several tools to obtain the prediction result. Benefit of this is that the weaknesses of one program can be compensated by others and therefore the result is expected to be more reliable than obtained by individual programs

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Tools predicting problems in MRNA splicing and their effect on disease susceptibility

All genomic variations can potentially be deleterious by affecting normal pre-mRNA splicing.However it is not possible to functionally test all of these variants and so it is important to restrict the search to those that are the most appropriate cases. Several tools exist for this purpose. Combined usage of the programs is recommended, because the weaknesses of one in silico tool may be overcome by the results of another tool (Houdayer et al 2008). This section also describes some other tools which evaluate the effect of SNPs on RNA level. 

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Tools considering epistatic effects and disease susceptibility associated with them

Epistatic interactions of SNPs are believed to be very important in determining individual susceptibility to complex diseases.Multiple genetic variations may show little effect individually but strong interactions jointly which is known as epistasis or multilocus interaction (Cordell et al 2002).Therefore the detection of epistatic interactions may help to reveal the underlying mechanisms behind complex disease. This page describes methods which predict these interactions.

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Tools and methods for mapping genomic structural variation

The page aims to collect tools and techniques related to variation identification and mapping from next generation sequencing data.  

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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.

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SNP identification and annotation tools

This section collects together tools that help identifying and annotation of SNPs. In addition they can be used to map SNPs to genes.

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Review Articles

• Bing Yu. Role of In SilicoTools in Gene Discovery. Mol Biotechnol. 2009 Mar;41(3):296-306. doi:10.1007/s12033-008-9134-8
• Karchin et al. Next generation tools for the annotation of human SNPs. Brief Bioinform. 2009 Jan;10(1):35-52. doi: 10.1093/bib/bbn047
• Tucker et al. Massively Parallel Sequencing: The Next Big Thing in Genetic Medicine.Am.J.Hum.Genet., 2009, 85, 2, 142-154. doi: 10.1016/j.ajhg.2009.06.022
• Wray et al. Prediction of individual genetic risk of complex disease.Curr.Opin.Genet.Dev., 2008, 18, 3, 257-263. doi:10.1016/j.gde.2008.07.006

Useful links

• Sage Commons Project
• Useful SNP related links from The Cuckoo Workgroup
• Cancer Genomics Tools including link to tools like Breakdancer, MAQ and several others
• Mutalyzer (tool to check that your sequence variation is coded as recommended by HGVS)
• SNPedia (SNPedia is a wiki site containing information about the effects of variations in DNA, citing peer-reviewed scientific publications)
• HuGE Navigator ( An integrated, searchable knowledge base of genetic associations and human genome epidemiology)
• NHGRI GWAS Catalog (article:doi: 10.1073/pnas.0903103106.)

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