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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Veröffentlicht in:Genome Biol
Hauptverfasser: 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
Format: Artigo
Sprache:Inglês
Veröffentlicht: BioMed Central 2019
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Online Zugang: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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