propr (3.0.4)

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 two metrics, phi [Lovell et al (2015) ] and rho [Erb and Notredame (2016) ], to provide a valid alternatives to correlation for relative data. Unlike correlation, these metrics give the same result for both relative and absolute data. Pairs that are strongly proportional in relative space are also strongly correlated in absolute space. Proportionality avoids the pitfall of spurious correlation.

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

License: GPL-2

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

Released over 2 years ago.