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: | 1.0 |
| Depends: | R (≥ 3.4.0) |
| Imports: | plyr (≥ 1.8.4), foreach (≥ 1.4.4), doParallel (≥ 1.0.11), pcaMethods (≥ 1.70.0), ggplot2 (≥ 2.2.1), gridExtra (≥ 2.3), reshape2 (≥ 1.4.3), iterators (≥ 1.0.9), shiny (≥ 1.0.5), shinythemes (≥ 1.1.1) |
| Suggests: | knitr, rmarkdown, pander, R.rsp |
| Published: | 2018-01-24 |
| Author: | Arnaud Wolfer [aut, cre], Timothy Ebbels [ctb], Joe Cheng [ctb] (Shiny javascript custom-input control) |
| Maintainer: | Arnaud Wolfer <adwolfer at gmail.com> |
| License: | GPL-3 |
| URL: | https://github.com/adwolfer |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | santaR results |
| Reference manual: | santaR.pdf |
| Vignettes: |
Advanced command line functions Automated command line analysis Getting Started with the santaR package Plotting options How to prepare input data for santaR Selecting an optimal number of degrees of freedom santaR Theoretical Background santaR: Graphical user interface |
| Package source: | santaR_1.0.tar.gz |
| Windows binaries: | r-devel: santaR_1.0.zip, r-release: santaR_1.0.zip, r-oldrel: santaR_1.0.zip |
| macOS binaries: | r-release: santaR_1.0.tgz, r-oldrel: santaR_1.0.tgz |
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