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. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 3 times.
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Last 365 days
This package has been downloaded 1,954 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Sep 11, 2024 with 26 downloads.
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Dependencies
- Imports1 package
- Suggests1 package