RegSNPs-intron: a computational framework for predicting pathogenic impact of intronic single nucleotide variants

Single nucleotide variants (SNVs) in intronic regions have yet to be systematically investigated for their disease-causing potential. Using known pathogenic and neutral intronic SNVs (iSNVs) as training data, we develop the RegSNPs-intron algorithm based on a random forest classifier that integrates...

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Salvato in:
Dettagli Bibliografici
Pubblicato in:Genome Biol
Autori principali: Lin, Hai, Hargreaves, Katherine A., Li, Rudong, Reiter, Jill L., Wang, Yue, Mort, Matthew, Cooper, David N., Zhou, Yaoqi, Zhang, Chi, Eadon, Michael T., Dolan, M. Eileen, Ipe, Joseph, Skaar, Todd C., Liu, Yunlong
Natura: Artigo
Lingua:Inglês
Pubblicazione: BioMed Central 2019
Soggetti:
Method
Accesso online:https://ncbi.nlm.nih.gov/pmc/articles/PMC6883696/
https://ncbi.nlm.nih.gov/pubmed/31779641
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s13059-019-1847-4
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