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) <DOI:10.1371/journal.pcbi.1004075>]
and rho [Erb and Notredame (2016) <DOI:10.1007/s12064-015-0220-8>], 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.
fastcluster, ggplot2, igraph, Rcpp, stats, utils

c(
person("Thomas", "Quinn", email = "contacttomquinn@gmail.com", role = c("aut", "cre")),
person("David", "Lovell", email = "david.lovell@qut.edu.au", role = "aut"),
person("Ionas", "Erb", email = "ionas.erb@crg.eu", role = "aut"),
person("Anders", "Bilgrau", email = "anders.ellern.bilgrau@gmail.com", role = "ctb"),
person("Greg", "Gloor", email = "ggloor@uwo.ca", role = "ctb")
)
fastcluster, ggplot2, grDevices, igraph, Rcpp, stats, utils
ALDEx2, cccrm, compositions, data.table, datasets,
directlabels, grid, ggdendro, knitr, limma, plotly, reshape2,
rgl, rmarkdown, SDMTools, testthat
Thomas Quinn [aut, cre],
David Lovell [aut],
Ionas Erb [aut],
Anders Bilgrau [ctb],
Greg Gloor [ctb]

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.