wrGraph: Graphics in the Context of Analyzing High-Throughput Data
Additional options for making graphics in the context of analyzing high-throughput data are available here.
This includes automatic segmenting of the current device (eg window) to accommodate multiple new plots,
automatic checking for optimal ___location of legends in plots, small histograms to insert as legends,
histograms re-transforming axis labels to linear when plotting log2-transformed data,
a violin-plot <doi:10.1080/00031305.1998.10480559> function for a wide variety of input-formats,
principal components analysis (PCA) <doi:10.1080/14786440109462720> with bag-plots <doi:10.1080/00031305.1999.10474494>
to highlight and compare the center areas for groups of samples,
generic MA-plots (differential- versus average-value plots) <doi:10.1093/nar/30.4.e15>,
staggered count plots and generation of mouse-over interactive html pages.
| Version: |
1.3.18 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
graphics, grDevices, grid, lattice, RColorBrewer, stats, wrMisc (> 2.0.1) |
| Suggests: |
dplyr, factoextra, FactoMineR, ggpubr, knitr, limma, rmarkdown, sm |
| Published: |
2026-09-03 |
| DOI: |
10.32614/CRAN.package.wrGraph |
| Author: |
Wolfgang Raffelsberger [aut, cre] |
| Maintainer: |
Wolfgang Raffelsberger <w.raffelsberger at gmail.com> |
| License: |
GPL-3 |
| NeedsCompilation: |
no |
| Materials: |
NEWS |
| CRAN checks: |
wrGraph results |
Documentation:
Downloads:
Reverse dependencies:
Linking:
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