bioRxiv
mSigHdp: hierarchical Dirichlet process mixture modeling for mutational signature discovery
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, Preprint
Liu, M; Wu, Y; Jiang, N; Boot, A; Rozen, S
2022
Duke Scholars
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Liu, M., Wu, Y., Jiang, N., Boot, A., & Rozen, S. (2022). mSigHdp: hierarchical Dirichlet process mixture modeling for mutational signature discovery. bioRxiv. https://doi.org/10.1101/2022.01.31.478587
Liu, Mo, Yang Wu, Nanhai Jiang, Arnoud Boot, and Steven Rozen. “mSigHdp: hierarchical Dirichlet process mixture modeling for mutational signature discovery.” BioRxiv, 2022. https://doi.org/10.1101/2022.01.31.478587.
Liu M, Wu Y, Jiang N, Boot A, Rozen S. mSigHdp: hierarchical Dirichlet process mixture modeling for mutational signature discovery. bioRxiv. 2022.
Liu, Mo, et al. “mSigHdp: hierarchical Dirichlet process mixture modeling for mutational signature discovery.” BioRxiv, 2022. Epmc, doi:10.1101/2022.01.31.478587.
Liu M, Wu Y, Jiang N, Boot A, Rozen S. mSigHdp: hierarchical Dirichlet process mixture modeling for mutational signature discovery. bioRxiv. 2022.