PredictSNP 2.0

PredictSNP 2.0

software

Use of the result by another entity is possible without acquiring a license in some cases

The licensor does not require a license fee for the result

Bendl Jaroslav, Ing., Ph.D.
Musil Miloš, Ing., Ph.D. (DIFS)
Štourač Jan (FIT)
Zendulka Jaroslav, doc. Ing., CSc. (UIFS)
Damborský Jiří, prof. Mgr., Dr. (UMEL)
Brezovský Jan (FIT)

SNP effect; deleteriousness prediction; SNP prediction; mutation analysis; Mendelian diseases

This tool estimates the deleteriousness of single-nucleotide mutations in the context of the development of Mendelian diseases. The predictions are based on the results of existing tools: CADD, DANN, FATHMM, FunSeq2 and GWAVA. To achieve the highest possible accuracy, developed consensual functions based on category optimal decision thresholds differ according to the category of variants. These general categories are recognized: (i) regulatory, (ii) splicing, (iii) synonymous, (iv) missense and (v)nonsense variants. The evaluation on large datasets revealed a marked benefit of this approach while the web interface provides easily interpretable results for all individual tools and our consensual prediction together with the links to the relevant databases and on-line services.

Nástroj je dostupný na internetové adrese:http://loschmidt.chemi.muni.cz/predictsnp2/Uživatelský manuál je dostupný na internetové adrese:http://loschmidt.chemi.muni.cz/predictsnp2/docs/userguide.pdf

Výzkum pokročilých metod ICT a jejich aplikace, BUT, Vnitřní projekty VUT, FIT-S-14-2299, 2014-2016, completed

Information and Database Systems Research Group (RG IS)

Department of Information Systems (DIFS)