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 <contacttomquinn at gmail.com>

Author(s): Thomas Quinn*, David Lovell*, Ionas Erb*, Anders Bilgrau*, Greg Gloor*

Install package and any missing dependencies by running this line in your R console:

install.packages("propr")

Depends methods, R (>= 3.2.2)
Imports fastcluster, ggplot2, grDevices, igraph, Rcpp, stats, utils
Suggests ALDEx2, cccrm, compositions, data.table, datasets, directlabels, grid, ggdendro, knitr, limma, plotly, reshape2, rgl, rmarkdown, SDMTools, testthat
Enhances
Linking to Rcpp
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Package propr
Materials
URL http://github.com/tpq/propr
Task Views
Version 3.0.4
Published 2017-06-02
License GPL-2
BugReports http://github.com/tpq/propr/issues
SystemRequirements
NeedsCompilation yes
Citation
CRAN checks propr check results
Package source propr_3.0.4.tar.gz