Package: TMixClust 1.35.0

Monica Golumbeanu

TMixClust: Time Series Clustering of Gene Expression with Gaussian Mixed-Effects Models and Smoothing Splines

Implementation of a clustering method for time series gene expression data based on mixed-effects models with Gaussian variables and non-parametric cubic splines estimation. The method can robustly account for the high levels of noise present in typical gene expression time series datasets.

Authors:Monica Golumbeanu <[email protected]>

TMixClust_1.35.0.tar.gz
TMixClust_1.35.0.zip(r-4.7)TMixClust_1.35.0.zip(r-4.6)TMixClust_1.35.0.zip(r-4.5)
TMixClust_1.35.0.tgz(r-4.6-any)TMixClust_1.35.0.tgz(r-4.5-any)
TMixClust_1.35.0.tar.gz(r-4.7-any)TMixClust_1.35.0.tar.gz(r-4.6-any)
TMixClust_1.35.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
TMixClust/json (API)

# Install 'TMixClust' in R:

install.packages('TMixClust', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

best_clust_toy_obj - TMixClust object containing the optimal clustering solution for the toy data with 3 clusters.
best_clust_yeast_obj - TMixClust object containing the optimal clustering solution for the yeast data.
toy_data_df - Simulated time-series gene expression data

On BioConductor:TMixClust-1.35.0(bioc 3.24)TMixClust-1.34.0(bioc 3.23)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

software statisticalmethod clustering timecourse geneexpression

3.60 score 9 scripts 2 mentions 7 exports 33 dependencies

Last updated from:938d5d18b3. Checks:1 ERROR, 9 OK. Indexed: yes.

Target	Result	Time
bioc-checks	ERROR	155
linux-devel-x86_64	OK	189
source / vignettes	OK	178
linux-release-x86_64	OK	220
macos-release-arm64	OK	112
macos-oldrel-arm64	OK	114
windows-devel	OK	108
windows-release	OK	121
windows-oldrel	OK	111
wasm-release	OK	163

Exports:analyse_stability generate_TMixClust_report get_time_series_df get_time_series_df_bio plot_silhouette plot_time_series_df TMixClust

Dependencies:BH Biobase BiocGenerics BiocParallel class cluster codetools cpp11 digest flexclust formatR futile.logger futile.options future future.apply generics globals gss lambda.r lattice listenv MASS modeltools mvtnorm numDeriv parallelly Rcpp RcppArmadillo Rsolnp snow SPEM truncnorm zoo

Clustering time series gene expression data with TMixClust

1 Standard workflow applied to simulated and real data | 2 Methodology behind TMixClust | 3 How to get help | 4 Session info | 5 Citing this package

Rendered fromTMixClust.Rnwusingknitr::knitr

Last update: 2018-02-01
Started: 2017-07-11

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
The main usages of TMixClust	TMixClust-package
Stability analysis, clustering evaluation and optimal solution selection	analyse_stability
TMixClust object containing the optimal clustering solution for the toy data with 3 clusters.	best_clust_toy_obj
TMixClust object containing the optimal clustering solution for the yeast data.	best_clust_yeast_obj
Generates a series of files containing a summary of the TMixClust analysis results	generate_TMixClust_report
Extracts a time series data frame from a text file	get_time_series_df
Extracts a time series data frame from a Bioconductor Biobase ExpressionSet object.	get_time_series_df_bio
Generates a silhouette plot for a given clustering configuration.	plot_silhouette
Plots all the time series stored in a data frame object	plot_time_series_df
Clusters the time series data in a given number of groups	TMixClust
Simulated time-series gene expression data	toy_data_df