Package: cancerGI 1.0.1

cancerGI: Analyses of Cancer Gene Interaction

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>.

Authors:Audrey Qiuyan Fu and Xiaoyue Wang

cancerGI_1.0.1.tar.gz
cancerGI_1.0.1.zip(r-4.7)cancerGI_1.0.1.zip(r-4.6)cancerGI_1.0.1.zip(r-4.5)
cancerGI_1.0.1.tgz(r-4.6-any)cancerGI_1.0.1.tgz(r-4.5-any)
cancerGI_1.0.1.tar.gz(r-4.7-any)cancerGI_1.0.1.tar.gz(r-4.6-any)
cancerGI_1.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
cancerGI/json (API)

# Install 'cancerGI' in R:

install.packages('cancerGI', repos = c('https://audreyqyfu.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

mutations - Genetic mutation data in patients.
RNAi - Molecular phenotypes from single and double knockdowns in RNAi screen
survival - Patient survival data.
tested_pairs - Gene pairs tested in the double knockdown assay.

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 212 downloads 8 exports 75 dependencies

Last updated from:6ec6ae0c5b. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	202
source / vignettes	OK	188
linux-release-x86_64	OK	155
macos-release-arm64	OK	152
macos-oldrel-arm64	OK	116
windows-devel	OK	103
windows-release	OK	118
windows-oldrel	OK	99
wasm-release	OK	118

Exports:computeSmallWorldness computeSurvivalPValueForGenePairSet.output computeSurvivalPValueGenePairAll.output computeSurvivalPValueOneGenePair computeSurvivalPValueOneGenePair.output constructDesignMatrix processDataMutSurv testMutationalPatternAll.wrapper

Dependencies:abind backports boot broom car carData cli colorspace cowplot cpp11 Deriv doBy dplyr farver forecast Formula fracdiff generics ggplot2 glue gtable igraph isoband labeling lattice lifecycle lme4 lmtest magrittr MASS Matrix MatrixModels mgcv microbenchmark minqa modelr nlme nloptr nnet numDeriv pbkrtest pillar pkgconfig plyr purrr quantreg qvalue R6 rbibutils RColorBrewer Rcpp RcppArmadillo RcppEigen Rdpack reformulas reshape2 rlang S7 sandwich scales SparseM stringi stringr survival systemfit tibble tidyr tidyselect timeDate urca utf8 vctrs viridisLite withr zoo

Help page	Topics
Compute smallworldness of a graph	computeSmallWorldness
Survival analysis for pairs of genes	computeSurvivalPValueForGenePairSet.output
Survival analysis for pairs of genes (with matched individuals)	computeSurvivalPValueGenePairAll.output
Survival analysis for one pair of genes	computeSurvivalPValueOneGenePair
Write results from survival analysis to output for one pair of genes	computeSurvivalPValueOneGenePair.output
Generate a design matrix from raw RNAi data.	constructDesignMatrix
Genetic mutation data in patients.	mutations
Find matched individuals in mutation and survival data	processDataMutSurv
Molecular phenotypes from single and double knockdowns in RNAi screen	RNAi
Patient survival data.	survival
Gene pairs tested in the double knockdown assay.	tested_pairs
Compute the p and q values of all pairwise gene mutation patterns	testMutationalPatternAll.wrapper

Package: cancerGI 1.0.1

cancerGI: Analyses of Cancer Gene Interaction

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Readme and manuals

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