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.
- Version2.0.3
- R version≥ 2.10
- LicenseApache License (== 2.0)
- Needs compilation?No
- Last release05/03/2022
Documentation
Team
Kevin R. Coombes
MaintainerShow author detailsPan Tong
Insights
Last 30 days
This package has been downloaded 155 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 3 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 1,947 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Sep 11, 2024 with 26 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports1 package
- Suggests1 package