SIBERG
Systematic Identification of Bimodally Expressed Genes Using RNAseq Data
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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
2.0.4 |
rolling linux/jammy R-4.5 | SIBERG_2.0.4.tar.gz |
194.0 KiB |
2.0.4 |
rolling linux/noble R-4.5 | SIBERG_2.0.4.tar.gz |
193.9 KiB |
2.0.4 |
rolling source/ R- | SIBERG_2.0.4.tar.gz |
152.8 KiB |
2.0.4 |
latest linux/jammy R-4.5 | SIBERG_2.0.4.tar.gz |
194.0 KiB |
2.0.4 |
latest linux/noble R-4.5 | SIBERG_2.0.4.tar.gz |
193.9 KiB |
2.0.4 |
latest source/ R- | SIBERG_2.0.4.tar.gz |
152.8 KiB |
2.0.4 |
2026-04-26 source/ R- | SIBERG_2.0.4.tar.gz |
152.8 KiB |
2.0.4 |
2026-04-23 source/ R- | SIBERG_2.0.4.tar.gz |
152.8 KiB |
2.0.4 |
2026-04-09 windows/windows R-4.5 | SIBERG_2.0.4.zip |
197.7 KiB |
2.0.4 |
2025-04-20 source/ R- | SIBERG_2.0.4.tar.gz |
152.8 KiB |