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parafac4microbiome

Parallel Factor Analysis Modelling of Longitudinal Microbiome Data

v1.3.2 · Jul 31, 2025 · MIT + file LICENSE

Description

Creation and selection of PARAllel FACtor Analysis (PARAFAC) models of longitudinal microbiome data. You can import your own data with our import functions or use one of the example datasets to create your own PARAFAC models. Selection of the optimal number of components can be done using assessModelQuality() and assessModelStability(). The selected model can then be plotted using plotPARAFACmodel(). The Parallel Factor Analysis method was originally described by Caroll and Chang (1970) <doi:10.1007/BF02310791> and Harshman (1970) <https://www.psychology.uwo.ca/faculty/harshman/wpppfac0.pdf>.

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NOTE 13 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026
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package dependencies

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Dependency Network

Dependencies Reverse dependencies compositions cowplot doParallel dplyr foreach ggplot2 ggpubr lifecycle magrittr multiway pracma rlang rTensor tidyr NPLStoolbox CMTFtoolbox parafac4microbiome

Version History

new 1.3.2 Mar 10, 2026
updated 1.3.2 ← 1.2.1 diff Jul 30, 2025
updated 1.2.1 ← 1.1.2 diff May 19, 2025
updated 1.1.2 ← 1.0.3 diff Mar 21, 2025
updated 1.0.3 ← 1.0.2 diff Sep 23, 2024
new 1.0.2 Sep 16, 2024