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Giulio Caravagna edited this page Sep 25, 2018 · 9 revisions

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MOBSTER - Model-based subclonal clustering in cancer - combines the theory of Population Genetics with standard Machine Learning in order to learn the clonal structure of a cancer population from read counts of bulk sequencing.

Compared to previous methods, MOBSTER exploits the distributions that we know to arise from cancer's growth, and computes better fits that can improve our current evolutionary analysis of bulk samples.

  • G. Caravagna, et al. In preparation.

Current version: NA

Author: Giulio Caravagna [@gcaravagna], Institute of Cancer Research, UK.

For any query about the tool, contact [email protected]; for requests of support open an issue here on Github

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