SMuRF: portable and accurate ensemble prediction of somatic mutations

SUMMARY: Somatic Mutation calling method using a Random Forest (SMuRF) integrates predictions and auxiliary features from multiple somatic mutation callers using a supervised machine learning approach. SMuRF is trained on community-curated matched tumor and normal whole genome sequencing data. SMuRF...

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Detalles Bibliográficos
Autores principales: Huang, Weitai, Guo, Yu Amanda, Muthukumar, Karthik, Baruah, Probhonjon, Chang, Mei Mei, Jacobsen Skanderup, Anders
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Applications Notes
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6735703/
https://www.ncbi.nlm.nih.gov/pubmed/30649191
http://dx.doi.org/10.1093/bioinformatics/btz018

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6735703/
https://www.ncbi.nlm.nih.gov/pubmed/30649191
http://dx.doi.org/10.1093/bioinformatics/btz018

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