Packaged: 2021-10-21 10:48:51 UTC; dmitry.shkolnik

Packaged: 2021-10-28 14:55:00 UTC; dmitry.shkolnik

Title: Analyses of Cancer Gene Interaction
Author: Audrey Qiuyan Fu and Xiaoyue Wang
Description: Functions to perform the following analyses: i) inferring epistasis from RNAi double knockdown data; ii) identifying gene pairs of multiple mutation patterns; iii) assessing association between gene pairs and survival; and iv) calculating the smallworldness of a graph (e.g., a gene interaction network).  Data and analyses are described in Wang, X., Fu, A. Q., McNerney, M. and White, K. P. (2014). Widespread genetic epistasis among breast cancer genes. Nature Communications. 5 4828. <doi:10.1038/ncomms5828>.
Imports: systemfit, qvalue, survival, reshape2, igraph

Title: Estimation of temporal ordering of cancer abnormalities
Description: This is a package with functions for timing copy number
changes using estimates of mutational allele frequency from
Depends: R (>= 2.11.0), LearnBayes, GenomicRanges

Description: This is a package with functions for timing copy number changes using estimates of mutational allele frequency from resequencing of tumor samples.

Title: Estimation of Temporal Ordering of Cancer Abnormalities

Imports: utils, stats, grDevices, graphics, LearnBayes, gplots

Description: Timing copy number changes using estimates of mutational allele frequency from resequencing of tumor samples.

Suggests: GenomicRanges (>= 1.23.23), IRanges (>= 2.5.39)

Title: Generalized Canonical Discriminant Analysis
Description: Functions for computing and graphing canonical discriminant
Packaged: Sun Nov  9 04:52:31 2008; theussl

Depends: car, heplots (>= 0.8-3), graphics, stats
Packaged: Mon Feb  2 17:34:38 2009; rforge

Description: Functions for computing and graphing canonical

Depends: car, heplots (>= 0.8-6), graphics, stats

Depends: R (>= 2.10), car, heplots (>= 0.8.6), graphics, stats

Packaged: Mon Apr 14 08:47:44 2008; John Fox

Title: Visualizing Generalized Canonical Discriminant and Canonical
Description: This package includes functions for computing and
visualizing generalized canonical discriminant analyses for a
multivariate linear model.  Traditional canonical discriminant
analysis is restricted to a one-way MANOVA design and is
equivalent to canonical correlation analysis between a set of
quantitative response variables and a set of dummy variables
coded from the factor variable.  The candisc package
generalizes this to multi-way MANOVA designs for all factors in
a multivariate linear model, computing canonical scores and
vectors for each term. The graphic functions provide low-rank
(1D, 2D, 3D) visualizations of terms in an mlm via the