SMuRFv2

Name of software SMuRFv2 
Purpose Somatic mutation calling using a RandomForest machine learning approach
Name of Contact Huang Weitai & Anders Skanderup
Email of technical contact huangwt@gis.a-star.edu.sg
skanderupamj@gis.a-star.edu.sg
Summary of software function

Somatic mutation calling using a RandomForest machine learning approach

SMuRFv2 is freely available for academic use. Commercial usage requires a license.
Publications describing software & its application Huang et al. (2022) Accurate ensemble prediction of somatic mutations with SMuRF2. Methods in Molecular Biology: Variant Calling.

Huang et al. (2020) Ensemble-Based Somatic Mutation Calling in Cancer Genomes. Methods in Molecular Biology: Bioinformatics for Cancer Immunotherapy.

Huang et al. (2019) SMuRF: Portable and accurate ensemble prediction of somatic mutations. Bioinformatics.

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