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DESCRIPTION
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Package: parafac4microbiome
Title: Parallel Factor Analysis Modelling of Longitudinal Microbiome Data
Version: 1.0.3
Authors@R: c(
person("Geert Roelof", "van der Ploeg", , "g.r.ploeg@uva.nl", role = c("aut", "cre"),
comment = c(ORCID = "0009-0007-5204-3386")),
person("Johan", "Westerhuis", , "j.a.westerhuis@uva.nl", role = "ctb",
comment = c(ORCID = "0000-0002-6747-9779")),
person("Anna", "Heintz-Buschart", , "a.u.s.heintzbuschart@uva.nl", role = "ctb",
comment = c(ORCID = "0000-0002-9780-1933")),
person("Age", "Smilde", , "a.k.smilde@uva.nl", role = "ctb",
comment = c(ORCID = "0000-0002-3052-4644")),
person("University of Amsterdam", role = c("cph", "fnd")))
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>.
License: MIT + file LICENSE
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2
Imports:
compositions,
cowplot,
doParallel,
dplyr,
foreach,
ggplot2,
ggpubr,
lifecycle,
magrittr,
methods,
mize,
multiway,
parallel,
pracma,
rlang,
rTensor,
stats,
tidyr
Depends:
R (>= 2.10)
LazyData: true
Suggests:
knitr,
MicrobiotaProcess,
phyloseq,
rmarkdown,
SummarizedExperiment,
testthat (>= 3.0.0),
TreeSummarizedExperiment,
withr
Config/testthat/edition: 3
VignetteBuilder: knitr
URL: https://grvanderploeg.github.io/parafac4microbiome/, https://github.com/GRvanderPloeg/parafac4microbiome
BugReports: https://github.com/GRvanderPloeg/parafac4microbiome/issues