Package: propr
Title: Calculating Proportionality Between Vectors of Compositional
        Data
Version: 3.1.1
URL: http://github.com/tpq/propr
BugReports: http://github.com/tpq/propr/issues
Authors@R: 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")
    )
Description: 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.
License: GPL-2
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 6.0.1
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
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2017-11-13 06:07:07 UTC; thom
Author: Thomas Quinn [aut, cre],
  David Lovell [aut],
  Ionas Erb [aut],
  Anders Bilgrau [ctb],
  Greg Gloor [ctb]
Maintainer: Thomas Quinn <contacttomquinn@gmail.com>
Repository: CRAN
Date/Publication: 2017-11-13 06:24:32 UTC
