The rapidly decreasing prices for sequencing entire human exomes and genomes resulted in large amounts of variation data. To cope with this variation data we developed snpActs, a database-driven toolset that allows scientists to annotate single nucleotide variants (SNVs) and to categorize them comprehensively. snpActs scans different gene annotations and identifies SNVs in functional elements. Additionally, snpActs utilizes the results of several established mutation effect prediction algorithms, such as SNAP, SIFT, and Polyphen2, to distinguish between deleterious and functionally neutral amino acid changes caused by SNVs. For this, it also checks the Human Gene Mutation Database (HGMD). In comparison to other annotation-programs snpActs can filter SNVs lists can be filtered using special rules (e.g. coding SNVs), special masks (e.g. cancer regions) or based upon other SNV lists (e.g. presence in relatives). snpActs further implements a classical and precise linkage analysis to examine regions that are identity-by-descent in data sets from complex pedigrees. Via these functionalities it is possible to identify potential disease causing genes in examined individuals.
The following tools are integrated in the snpActs tool set:
- snpAct: analyze and categorize SNVs
- filterAct: filter tools to reduce SNVs through special masks or other SNP lists
- targetAct: filter tool to reduce SNVs through special target regions
- mergeAct: merge SNV lists to compare SNVs easily
- concordanceAct: overlap/concordance calculations
- outputAct: several output formats i.e. for statistics or resequencing
- sexAct / mendelAct: determine the gender and check the Mendel-errors of a sample
- ibdAct: pipeline to identify linked SNVs in pedigrees
- blurAct: aggregate SNV-data to share them with the research community using grabBlur
For more information visit our snpActs homepage.