Package: MVisAGe 0.2.1

MVisAGe: Compute and Visualize Bivariate Associations

Pearson and Spearman correlation coefficients are commonly used to quantify the strength of bivariate associations of genomic variables. For example, correlations of gene-level DNA copy number and gene expression measurements may be used to assess the impact of DNA copy number changes on gene expression in tumor tissue. 'MVisAGe' enables users to quickly compute and visualize the correlations in order to assess the effect of regional genomic events such as changes in DNA copy number or DNA methylation level. Please see Walter V, Du Y, Danilova L, Hayward MC, Hayes DN, 2018. Cancer Research <doi:10.1158/0008-5472.CAN-17-3464>.

Authors:Vonn Walter [aut, cre]

MVisAGe_0.2.1.tar.gz
MVisAGe_0.2.1.zip(r-4.7)MVisAGe_0.2.1.zip(r-4.6)MVisAGe_0.2.1.zip(r-4.5)
MVisAGe_0.2.1.tgz(r-4.6-any)MVisAGe_0.2.1.tgz(r-4.5-any)
MVisAGe_0.2.1.tar.gz(r-4.7-any)MVisAGe_0.2.1.tar.gz(r-4.6-any)
MVisAGe_0.2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
MVisAGe/json (API)

# Install 'MVisAGe' in R:

install.packages('MVisAGe', repos = c('https://vonnwalter23.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

cn.mat - DNA copy number data from 98 head and neck squamous cell carcinoma (HNSC) patients
exp.mat - Gene expression data from 100 head and neck squamous cell carcinoma (HNSC) patients
gene.annot - Gene annotation data
sample.annot - Sample annotation data

On CRAN:

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

2.74 score 11 scripts 235 downloads 11 exports 0 dependencies

Last updated from:999e6fac45. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	102
source / vignettes	OK	133
linux-release-x86_64	OK	110
macos-release-arm64	OK	96
macos-oldrel-arm64	OK	98
windows-devel	OK	94
windows-release	OK	78
windows-oldrel	OK	68
wasm-release	OK	87

Exports:cn.region.heatmap corr.compute corr.list.compute data.prep perm.significance perm.significance.list.compute smooth.genome.plot smooth.region.plot tcga.cn.convert tcga.exp.convert unsmooth.region.plot

Dependencies:

R packages: Static PDF vignettes

Rendered fromMVisAGe_vignette.pdf.asisusingR.rsp::asis

Last update: 2017-05-28
Started: 2017-05-28

Help page	Topics
DNA copy number data from 98 head and neck squamous cell carcinoma (HNSC) patients	cn.mat
A Function for Creating a Heatmap of DNA Copy Number Data	cn.region.heatmap
A Function for Computing a Vector of Pearson Correlation Coefficients	corr.compute
A Function for Creating a List of Pearson Correlation Coefficients	corr.list.compute
A Function for Preparing mRNAseq and Copy Number Data Matrices	data.prep
Gene expression data from 100 head and neck squamous cell carcinoma (HNSC) patients	exp.mat
Gene annotation data (hg38)	gene.annot
A Function for Computing a Vector of Pearson Correlation Coefficients	perm.significance
A Function for Creating a List of Pearson Correlation Coefficients	perm.significance.list.compute
Sample annotation data	sample.annot
A Function for Plotting Smoothed Pearson Correlation Coefficients Across Multiple Chromosomes	smooth.genome.plot
A Function for Plotting Smoothed Pearson Correlation Coefficients Genomewide	smooth.region.plot
A Function for Reformatting TCGA DNA Copy Number Matrices	tcga.cn.convert
A Function for Reformatting TCGA mRNA Expression Matrices	tcga.exp.convert
A Function for Plotting Pearson Correlation Coefficients in a Given Genomic Region	unsmooth.region.plot

Package: MVisAGe 0.2.1

MVisAGe: Compute and Visualize Bivariate Associations

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)