propr: Calculating Proportionality Between Vectors of Compositional Data

The bioinformatic evaluation of gene co-expression often begins with correlation-based analyses. However, this approach lacks statistical validity when applied to relative data, including those biological count data produced by microarray assays or high-throughput RNA-sequencing. Two metrics of proportionality, phi [Lovell et al (2015) <doi:10.1371/journal.pcbi.1004075>] and rho [Erb and Notredame (2016) <doi:10.1007/s12064-015-0220-8>], both derived from compositional data analysis, a branch of math dealing specifically with relative data, represent novel alternatives to correlation. This package introduces a programmatic framework for the calculation of feature dependence through proportionality, as discussed in the cited publications.

Version: 2.0.1
Depends: R (≥ 3.2.2)
Imports: methods, Rcpp
LinkingTo: Rcpp
Suggests: compositions, dendextend, ggplot2, ggthemes, knitr, rmarkdown, testthat
Published: 2016-09-30
Author: Thomas Quinn [aut, cre], David Lovell [aut]
Maintainer: Thomas Quinn <contacttomquinn at gmail.com>
BugReports: http://github.com/tpq/propr/issues
License: GPL-2
URL: http://github.com/tpq/propr
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: propr results

Downloads:

Reference manual: propr.pdf
Vignettes: Calculating the Proportionality Coefficients of Compositional Data
Package source: propr_2.0.1.tar.gz
Windows binaries: r-devel: propr_2.0.1.zip, r-release: propr_2.0.1.zip, r-oldrel: propr_2.0.1.zip
OS X Mavericks binaries: r-release: propr_2.0.1.tgz, r-oldrel: propr_2.0.1.tgz
Old sources: propr archive

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