A graphical and automated pipeline for the analysis of short time-series in R ('santaR'). This approach is designed to accommodate asynchronous time sampling (i.e. different time points for different individuals), inter-individual variability, noisy measurements and large numbers of variables. Based on a smoothing splines functional model, 'santaR' is able to detect variables highlighting significantly different temporal trajectories between study groups. Designed initially for metabolic phenotyping, 'santaR' is also suited for other Systems Biology disciplines. Command line and graphical analysis (via a 'shiny' application) enable fast and parallel automated analysis and reporting, intuitive visualisation and comprehensive plotting options for non-specialist users.
Version: 1.2.4 Depends: R (≥ 4.2) Imports: plyr (≥ 1.8.9), foreach (≥ 1.5.2), doParallel (≥ 1.0.17), pcaMethods (≥ 1.92.0), ggplot2 (≥ 3.5.0), gridExtra (≥ 2.3), reshape2 (≥ 1.4.3), iterators (≥ 1.0.9), shiny (≥ 1.8.0), bslib, DT (≥ 0.9) Suggests: knitr, rmarkdown, pander, R.rsp, testthat Published: 2024-03-07 DOI: 10.32614/CRAN.package.santaR Author: Arnaud Wolfer [aut, cre], Timothy Ebbels [ctb], Joe Cheng [ctb] (Shiny javascript custom-input control) Maintainer: Arnaud Wolfer <adwolfer at gmail.com> BugReports: https://github.com/adwolfer/santaR/issues/new License: GPL-3 URL: https://github.com/adwolfer/santaR, https://adwolfer.github.io/santaR/ NeedsCompilation: no Materials: README NEWS CRAN checks: santaR results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=santaR to link to this page.
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