HiLDA: a statistical approach to investigate differences in mutational signatures
We propose a hierarchical latent Dirichlet allocation model (HiLDA) for characterizing somatic mutation data in cancer. The method allows us to infer mutational patterns and their relative frequencies in a set of tumor mutational catalogs and to compare the estimated frequencies between tumor sets....
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
PeerJ Inc.
2019-08-01
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| Series: | PeerJ |
| Subjects: | |
| Online Access: | https://peerj.com/articles/7557.pdf |