Package: HTSCluster 2.0.11
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).
Authors:
HTSCluster_2.0.11.tar.gz
HTSCluster_2.0.11.zip(r-4.7)HTSCluster_2.0.11.zip(r-4.6)HTSCluster_2.0.11.zip(r-4.5)
HTSCluster_2.0.11.tgz(r-4.6-any)HTSCluster_2.0.11.tgz(r-4.5-any)
HTSCluster_2.0.11.tar.gz(r-4.7-any)HTSCluster_2.0.11.tar.gz(r-4.6-any)
HTSCluster_2.0.11.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
HTSCluster/json (API)
| # Install 'HTSCluster' in R: |
| install.packages('HTSCluster', repos = c('https://andreamrau.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/andreamrau/htscluster/issues
Last updated from:ca2ab810ac. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 166 | ||
| source / vignettes | OK | 190 | ||
| linux-release-x86_64 | OK | 168 | ||
| macos-release-arm64 | OK | 102 | ||
| macos-oldrel-arm64 | OK | 114 | ||
| windows-devel | OK | 99 | ||
| windows-release | OK | 98 | ||
| windows-oldrel | OK | 96 | ||
| wasm-release | OK | 127 |
Exports:emInithighDimensionARIHTSClusterUsersGuidekmeanInitlogLikePoisMixlogLikePoisMixDiffPoisMixClusPoisMixClusWrapperPoisMixMeanPoisMixSimprobaPostprobaPostInitsplitEMInit
Dependencies:capusheedgeRlatticelimmalocfitMASSplotrixstatmod
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Clustering high throughput sequencing (HTS) data | HTSCluster-package HTSCluster |
| Calculate ARI for high-dimensional data via data splits | highDimensionARI |
| View HTSCluster User's Guide | HTSClusterUsersGuide |
| Parameter initialization for a Poisson mixture model. | emInit kmeanInit probaPostInit splitEMInit |
| Log likelihood calculation for a Poisson mixture model | logLikePoisMix logLikePoisMixDiff mylogLikePoisMixObs |
| Visualize results from clustering using a Poisson mixture model | plot.HTSCluster plot.HTSClusterWrapper |
| Poisson mixture model estimation and model selection | PoisMixClus PoisMixClusWrapper |
| Calculate the conditional per-cluster mean of each observation | PoisMixMean |
| Simulate data from a Poisson mixture model | PoisMixSim |
| Calculate the conditional probability of belonging to each cluster in a Poisson mixture model | probaPost |
| Summarize results from clustering using a Poisson mixture model | summary.HTSCluster summary.HTSClusterWrapper |
