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

Bioconductor version: Release (3.19)

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.

Author: Monica Golumbeanu <golumbeanu.monica at>

Maintainer: Monica Golumbeanu <golumbeanu.monica at>

Citation (from within R, enter citation("TMixClust")):


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Clustering time series gene expression data with TMixClust PDF R Script
Reference Manual PDF


biocViews Clustering, GeneExpression, Software, StatisticalMethod, TimeCourse
Version 1.26.0
In Bioconductor since BioC 3.6 (R-3.4) (6.5 years)
License GPL (>=2)
Depends R (>= 3.4)
Imports gss, mvtnorm, stats, zoo, cluster, utils, BiocParallel, flexclust, grDevices, graphics, Biobase, SPEM
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Suggests rmarkdown, knitr, BiocStyle, testthat
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