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. This includes, for example, biological count data generated by high-throughput RNA-sequencing, chromatin immunoprecipitation (ChIP), ChIP-sequencing, Methyl-Capture sequencing, and other techniques. This package implements several metrics for proportionality, including phi [Lovell et al (2015) <doi:10.1371/journal.pcbi.1004075>] and rho [Erb and Notredame (2016) <doi:10.1007/s12064-015-0220-8>]. This package also implements several metrics for differential proportionality. Unlike correlation, these measures give the same result for both relative and absolute data.

Version: 3.0.7
Depends: methods, R (≥ 3.2.2)
Imports: fastcluster, ggplot2, grDevices, igraph, Rcpp, stats, utils
LinkingTo: Rcpp
Suggests: ALDEx2, cccrm, compositions, data.table, datasets, directlabels, grid, ggdendro, knitr, limma, plotly, reshape2, rgl, rmarkdown, SDMTools, testthat
Published: 2017-09-07
Author: Thomas Quinn [aut, cre], David Lovell [aut], Ionas Erb [aut], Anders Bilgrau [ctb], Greg Gloor [ctb]
Maintainer: Thomas Quinn <contacttomquinn at>
License: GPL-2
NeedsCompilation: yes
Citation: propr citation info
Materials: README NEWS
CRAN checks: propr results


Reference manual: propr.pdf
Vignettes: 1. An Introduction to Proportionality
2. Understanding Proportionality through Visualization
3. How Proportional Is Proportional Enough?
4. A Brief Critique of Proportionality
5. Calculating Differential Proportionality
Frequently Asked Questions
Package source: propr_3.0.7.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: propr_3.0.7.tgz
OS X Mavericks binaries: r-oldrel: propr_2.1.8.tgz
Old sources: propr archive


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