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>.

Version: 0.2.1
Depends: R (≥ 3.3.1)
Suggests: R.rsp
Published: 2018-05-10
Author: Vonn Walter [aut, cre]
Maintainer: Vonn Walter <vwalter1 at pennstatehealth.psu.edu>
License: GPL-3
NeedsCompilation: no
Materials: README NEWS
CRAN checks: MVisAGe results

Downloads:

Reference manual: MVisAGe.pdf
Vignettes: R packages: Static PDF vignettes
Package source: MVisAGe_0.2.1.tar.gz
Windows binaries: r-devel: MVisAGe_0.2.1.zip, r-release: MVisAGe_0.2.1.zip, r-oldrel: MVisAGe_0.2.1.zip
OS X binaries: r-release: MVisAGe_0.2.1.tgz, r-oldrel: MVisAGe_0.2.1.tgz
Old sources: MVisAGe archive

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