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Provides models to identify bimodally expressed genes from RNAseq data based on the Bimodality Index. SIBERG models the RNAseq data in the finite mixture modeling framework and incorporates mechanisms for dealing with RNAseq normalization. Three types of mixture models are implemented, namely, the mixture of log normal, negative binomial, or generalized Poisson distribution. See Tong et al. (2013) <doi:10.1093/bioinformatics/bts713>.
| Version: | 2.0.3 |
| Depends: | R (≥ 2.10) |
| Imports: | mclust |
| Suggests: | edgeR, doParallel |
| Published: | 2022-05-03 |
| Author: | Pan Tong, Kevin R. Coombes |
| Maintainer: | Kevin R. Coombes <krc at silicovore.com> |
| License: | Apache License (== 2.0) |
| URL: | http://oompa.r-forge.r-project.org/ |
| NeedsCompilation: | no |
| Materials: | NEWS |
| In views: | Omics |
| CRAN checks: | SIBERG results |
| Reference manual: | SIBERG.pdf |
| Vignettes: |
SIBER Vignette |
| Package source: | SIBERG_2.0.3.tar.gz |
| Windows binaries: | r-devel: SIBERG_2.0.3.zip, r-release: SIBERG_2.0.3.zip, r-oldrel: SIBERG_2.0.3.zip |
| macOS binaries: | r-release (arm64): SIBERG_2.0.3.tgz, r-oldrel (arm64): SIBERG_2.0.3.tgz, r-release (x86_64): SIBERG_2.0.3.tgz, r-oldrel (x86_64): SIBERG_2.0.3.tgz |
| Old sources: | SIBERG archive |
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