bioconductor-semisup
Semi-Supervised Mixture Model
Semi-Supervised Mixture Model
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Implements a parametric semi-supervised mixture model. The permutation test detects markers with main or interactive effects, without distinguishing them. Possible applications include genome-wide association analysis and differential expression analysis.
Summary
Semi-Supervised Mixture Model
Last Updated
Feb 7, 2026 at 00:35
License
GPL-3.0-only
Total Downloads
39.9K
Version Downloads
20
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Unsupported Platforms