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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Detalles Bibliográficos
Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Method
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6883696/
https://www.ncbi.nlm.nih.gov/pubmed/31779641
http://dx.doi.org/10.1186/s13059-019-1847-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6883696/
https://www.ncbi.nlm.nih.gov/pubmed/31779641
http://dx.doi.org/10.1186/s13059-019-1847-4

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