HTSCluster
Clustering High-Throughput Transcriptome Sequencing (HTS) Data
A Poisson mixture model is implemented to cluster genes from high-throughput transcriptome sequencing (RNA-seq) data. Parameter estimation is performed using either the EM or CEM algorithm, and the slope heuristics are used for model selection (i.e., to choose the number of clusters).
- Version2.0.11
- R versionunknown
- LicenseGPL (≥ 3)
- Needs compilation?No
- HTSCluster citation info
- Last release09/05/2023
Documentation
Team
Andrea Rau
Gilles Celeux
Marie-Laure Martin-Magniette
Cathy Maugis-Rabusseau
Insights
Last 30 days
This package has been downloaded 328 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 6 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 4,980 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 Jul 03, 2024 with 46 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
- Imports2 packages