Package: HH
Type: Package
Title: Statistical Analysis and Data Display: Heiberger and Holland
Version: 3.1-32
Date: 2016-06-22
Author: Richard M. Heiberger
Maintainer: Richard M. Heiberger <rmh@temple.edu>
Depends: R (>= 3.0.2), lattice, stats, grid, latticeExtra, multcomp, gridExtra (>= 2.0.0), graphics
Imports: reshape2, leaps, vcd, colorspace, RColorBrewer, shiny (>=
0.13.1), Hmisc, abind, Rmpfr (>= 0.6.0), grDevices, methods
Suggests: mvtnorm, car, Rcmdr, RcmdrPlugin.HH, TeachingDemos, microplot
Description: Support software for Statistical Analysis and Data Display (Second Edition, Springer, ISBN 978-1-4939-2121-8, 2015) and (First Edition, Springer, ISBN 0-387-40270-5, 2004) by Richard M. Heiberger and Burt Holland. This contemporary presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The second edition includes redesigned graphics and additional chapters. The authors emphasize how to construct and interpret graphs, discuss principles of graphical design, and show how accompanying traditional tabular results are used to confirm the visual impressions derived directly from the graphs. Many of the graphical formats are novel and appear here for the first time in print. All chapters have exercises. All functions introduced in the book are in the package. R code for all examples, both graphs and tables, in the book is included in the scripts directory of the package.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2016-06-22 04:32:23 UTC; rmh
Repository: CRAN
Date/Publication: 2016-06-23 01:13:28
Package: GOplot
Type: Package
Title: Visualization of Functional Analysis Data
Version: 1.0.2
Date: 2016-03-30
Authors@R: c(
person("Wencke", "Walter", , email = "wencke.walter@arcor.de", role = c("aut", "cre")),
person("Fatima", "Sanchez-Cabo", , role = "aut")
)
URL: https://github.com/wencke/wencke.github.io
BugReports: https://github.com/wencke/wencke.github.io/issues
Description: Implementation of multilayered visualizations for enhanced
graphical representation of functional analysis data. It combines and integrates
omics data derived from expression and functional annotation enrichment
analyses. Its plotting functions have been developed with an hierarchical
structure in mind: starting from a general overview to identify the most
enriched categories (modified bar plot, bubble plot) to a more detailed one
displaying different types of relevant information for the molecules in a given
set of categories (circle plot, chord plot, cluster plot, Venn diagram, heatmap).
Depends: ggplot2 (>= 2.0.0), ggdendro (>= 0.1-17), gridExtra (>=
2.0.0), RColorBrewer (>= 1.1.2), R (>= 3.2.3)
License: GPL-2
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
LazyData: TRUE
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-03-30 08:24:21 UTC; BioinfoNerd
Author: Wencke Walter [aut, cre],
Fatima Sanchez-Cabo [aut]
Maintainer: Wencke Walter <wencke.walter@arcor.de>
Repository: CRAN
Date/Publication: 2016-03-30 20:35:02
Package: ACSNMineR
Type: Package
Title: Gene Enrichment Analysis from ACSN Maps or GMT Files
Version: 0.16.01.29
Date: 2016-01-29
Authors@R: c(person("Paul", "Deveau", role = c("aut", "cre"),
email = "paul.deveau@curie.fr"),
person("Eric", "Bonnet",role = "aut",
email = "eric.bonnet@curie.fr"))
Maintainer: Paul Deveau <paul.deveau@curie.fr>
Description: Compute and represent gene set enrichment or depletion from your data based on pre-saved maps from the Atlas of Cancer Signalling Networks (ACSN) or user imported maps.
User imported maps must be complying with the GMT format as defined by the Broad Institute, that is to say that the file should be tab-separated, that the first column should contain the module name, the second column can contain comments that will be overwritten with the number of genes in the module, and subsequent columns must contain the list of genes (HUGO symbols; tab-separated) inside the module.
The gene set enrichment can be run with hypergeometric test or Fisher exact test, and can use multiple corrections.
Visualization of data can be done either by barplots or heatmaps.
Depends: R (>= 3.1.0), ggplot2, gridExtra, scales,
Suggests: knitr, rmarkdown,
License: GPL-2
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2016-02-12 10:01:07 UTC; User
Author: Paul Deveau [aut, cre],
Eric Bonnet [aut]
Repository: CRAN
Date/Publication: 2016-02-12 11:08:48
providing 
.