propr (2.1.2)

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 count data. This includes, for example, biological data produced by high-throughput RNA-sequencing, chromatin immunoprecipitation (ChIP), ChIP-sequencing, Methyl-Capture sequencing, and other techniques. Two metrics of proportionality, phi [Lovell et al (2015) ] and rho [Erb and Notredame (2016) ], 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 calculating feature dependence through proportionality, as discussed in the cited publications.

Maintainer: Thomas Quinn
Author(s): Thomas Quinn [aut, cre], David Lovell [aut], Anders Bilgrau [ctb], Ionas Erb [ctb]

License: GPL-2

Uses: fastcluster, ggplot2, Rcpp, compositions, igraph, data.table, testthat, reshape2, ggdendro, cccrm, knitr, rmarkdown, plotly
Reverse suggests: balance, exprso

Released over 2 years ago.