Meta tools are tools which combine the analysis of several other prediction tools. 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. This page lists meta tools currently available.
Pathogenic or NOT- pipeline (PON-P) is a meta tool that combines methods from the following categories: stability change prediction, aggregation prediction, disorder prediction and pathogenicity prediction. Inputs of the program can be given either as protein PDB code or FASTA formatted sequence and user can also include the list of mutations for analysis.
F-SNP is a meta tool spesifically prioritized for disease association studies. It uses in analysis 16 bioinformatics tools and databases. By using the tool one can make queries by using SNP ID, disease name, gene name or chromosomal region as an input. Output depends on analysis selected. By giving the SNP ID user gets information about its functional effects and by giving disease name the list of candidate gene list is given. A detailed description of meta tools function can be found from its website. Unfortunately it seems that the database versions (dbSNP, Ensembl, Gene and Disease and OMIM) are from year 2007 (which makes the results currently outdated) and no downloadble version of the tool is available as far as could be found.
Reference: Phil Hyoun Lee and Hagit Shatkay.F-SNP: computationally predicted functional SNPs for disease association studies.Nucleic Acids Res., January 2008; 36: D820 - D824. doi: http://dx.doi.org/10.1093/nar/gkm904
pfSNP integrates >40 different algorithms/resources to interrogate >14,000,000 SNPs from the dbSNP database for SNPs of potential functional significance based on previous published reports, inferred potential functionality from genetic approaches as well as predicted potential functionality from sequence motifs.
Reference: Wang et al.pfSNP: An integrated potentially functional SNP resource that facilitates hypotheses generation through knowledge syntheses. Hum Mutat. 2010 Jul 29. DOI: 10.1002/humu.21331
PolyDoms is an integrated database of human coding single nucleotide polymorphisms (SNPs) and their annotations. Unlike other databases of similar nature, apart from integrating several coding SNPs (cSNPs) and protein-related information resources, we predict the implications of the non-synonymous SNPs (nsSNPs) using two well known algorithms (SIFT and PolyPhen).
Reference: Jegga et al. PolyDoms: a whole genome database for the identification of non-synonymous coding SNPs with the potential to impact disease. Nucleic Acids Res., 2007, 35, Database issue, D700-6. doi: 10.1093/nar/gkl826.
MedRefSNP database provides integrated information about SNPs collected from the PubMed and OMIM databases. The RefSNP identifiers are automatically identified and are linked to various information sources such as the dbSNP, the HapMap database, the Entrez Gene database, the UCSC genome browser, the CGAP Pathway Searcher, and genetic association databases. And, each SNP is checked to determine whether the PolyDoms, SNPs3D or PolyPhen databases predicts that the SNP affects the phenotype of the protein encoded by the gene carrying the SNP. Also, neighboring SNPs showing strong linkage disequilibrium (LD) with published SNPs are included, using HapMap data. Unfortunately the link has outdated and the tool does not seem to be available anymore !
Reference: Rhee et al. MedRefSNP: a database of medically investigated SNPs. Hum.Mutat., 2009, 30, 3, E460-6. doi:10.1002/humu.20914
The SeattleSeq Annotation server provides annotation of SNPs (single-nucleotide polymorphisms), both known and novel. This annotation includes dbSNP rs ID, gene names and accession numbers, SNP functions (e.g. missense), protein positions and amino-acid changes, conservation scores, HapMap frequencies, PolyPhen predictions, and clinical association. Links to other annotation sites are also provided. Limited annotation for indels is also available.
SNPit is an integration system that allows you to search through multiple data sources and extract information on a whole range of possible predictors to functional SNPs. Data is extracted from dbSNP, EntrezGene, UCSC Browser, HGMD, ECR Browser, Haplotter, and SIFT.
Reference: Shen et al.SNPit: a federated data integration system for the purpose of functional SNP annotation.Comput Methods Programs Biomed. 2009 Aug;95(2):181-9. Epub 2009 Mar 26. doi:10.1016/j.cmpb.2009.02.010
The SNP Function Portal is designed to be a clearing house for all public domain SNP functional annotation data, as well as in-house functional annotations derived from different data sources. It currently contains SNP functional annotations in six major categories including genomic elements, transcription regulation, protein function, pathway, disease and population genetics. Besides extensive SNP functional annotations, the SNP Function Portal includes a powerful search engine that accepts different types of genetic markers as input and identifies all genetically related SNPs based on the HapMap Phase II data as well as the relationship of different markers to known genes.
website: SNP Function Portal
Reference: Wang et al. SNP Function Portal: a web database for exploring the function implication of SNP alleles.Bioinformatics. 2006 Jul 15;22(14):e523-9. doi: 10.1093/bioinformatics/btl241
Predicted Impact of Coding SNPs” database
(Database containing combained results from Polyphen, SIFT and Grantham matrix methods