DIME
Differential Identification using Mixture Ensemble
A robust identification of differential binding sites method for analyzing ChIP-seq (Chromatin Immunoprecipitation Sequencing) comparing two samples that considers an ensemble of finite mixture models combined with a local false discovery rate (fdr) allowing for flexible modeling of data. Methods for Differential Identification using Mixture Ensemble (DIME) is described in: Taslim et al., (2011) doi:10.1093/bioinformatics/btr165.
- Version1.3.0
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- Taslim et al., (2011)
- Last release05/09/2022
Team
Cenny Taslim
Dustin Potter
Abbasali Khalili
Shili Lin
Insights
Last 30 days
This package has been downloaded 246 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 11 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 3,213 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 35 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