Description: The method 'm:Explorer' associates a given list of target genes (e.g. those involved in a biological process) to gene regulators such as transcription factors. Transcription factors that bind DNA near significantly many target genes or correlate with target genes in transcriptional (microarray or RNAseq data) are selected. Selection of candidate master regulators is carried out using multinomial regression models, likelihood ratio tests and multiple testing correction. Reference: m:Explorer: multinomial regression models reveal positive and negative regulators of longevity in yeast quiescence. Juri Reimand, Anu Aun, Jaak Vilo, Juan M Vaquerizas, Juhan Sedman and Nicholas M Luscombe. Genome Biology (2012) 13:R55 <doi:10.1186/gb-2012-13-6-r55>.
Title: Identifying Master Gene Regulators from Gene Expression and
Imports: stats, utils, nnet, parallel, qusage
Packaged: 2017-08-24 13:27:51 UTC; dthompson

Title: Compute and Illustrate the Multiple Facets of Functional
Description: Computing functional traits-based distances between pairs of
species for species gathered in assemblages allowing to build several
functional spaces. The package allows to compute functional diversity
indices assessing the distribution of species (and of their dominance) in a
given functional space for each assemblage and the overlap between
assemblages in a given functional space, see: Chao et al. (2018)
<doi:10.1016/j.tpb.2009.10.001>. Graphical outputs are included.
Visit the 'mFD' website for more information, documentation and examples.
Imports: ade4, ape, betapart (>= 1.5.4), cluster, dendextend,
FactoMineR, gawdis, geometry, ggplot2, ggrepel, grid, Hmisc,
patchwork, reshape2, rstatix, stats, utils, vegan
Suggests: dplyr (>= 1.0.6), knitr, magrittr, rmarkdown (>= 2.6),
Author: Camille Magneville [aut, cre, cph]

Authors@R: person(given="Jesse", family="Hemerik", email="jesse.hemerik@wur.nl", role=c("aut", "cre"))
Description: Computes bounds for the median of the false discovery proportion (mFDP).
These 50 percent confidence bounds for the FDP are simultaneously valid.
The method takes a vector of p-values as input. Also provides mFDP-adjusted p-values.