doi:10.1007/BF02310791> and Harshman (1970) <https://www.psychology.uwo.ca/faculty/harshman/wpppfac0.pdf>.">

parafac4microbiome: Parallel Factor Analysis Modelling of Longitudinal Microbiome Data (original) (raw)

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>.

Version: 1.3.2
Depends: R (≥ 2.10)
Imports: compositions, cowplot, doParallel, dplyr, foreach, ggplot2, ggpubr, lifecycle, magrittr, methods, multiway, parallel, pracma, rlang, rTensor, stats, tidyr
Suggests: knitr, phyloseq, rmarkdown, TreeSummarizedExperiment (≥ 2.16.1), SummarizedExperiment (≥ 1.38.1), testthat (≥ 3.0.0), withr, NPLStoolbox
Published: 2025-07-31
DOI: 10.32614/CRAN.package.parafac4microbiome
Author: Geert Roelof van der PloegORCID iD [aut, cre], Johan Westerhuis ORCID iD [ctb], Anna Heintz-BuschartORCID iD [ctb], Age Smilde ORCID iD [ctb], University of Amsterdam [cph, fnd]
Maintainer: Geert Roelof van der Ploeg <g.r.ploeg at uva.nl>
BugReports: https://github.com/GRvanderPloeg/parafac4microbiome/issues
License: MIT + file
URL: https://grvanderploeg.com/parafac4microbiome/,https://github.com/GRvanderPloeg/parafac4microbiome/
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: parafac4microbiome results

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