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propr

swMATH ID: 15745
Software Authors: Thomas Quinn, David Lovell
Description: R package propr. The bioinformatic evaluation of gene co-expression often begins with correlation-based analyses. However, this approach lacks statistical validity when applied to relative data, including those biological count data produced by microarray assays or high-throughput RNA-sequencing. As an alternative, Lovell et al propose a proportionality metric, phi, derived from compositional data analysis, a branch of math dealing specifically with relative data. In a subsequent publication, Erb and Nicodemus expounded these efforts by elaborating on another proportionality metric, rho. This package introduces a programmatic framework for the calculation of feature dependence using proportionality and other compositional data methods discussed in the cited publications.
Homepage: https://cran.r-project.org/web/packages/propr/index.html
Dependencies: R
Keywords: bioinformatic; gene co-expression; RNA-sequencing
Related Software: NeatMap; betapart; INMEX; HMP; MetamicrobiomeR; MicrobiomeAnalyst; MDSINE; pplacer; UrQt; DOTUR; Voom; Phyloseq; robCompositions; RStudio; limma; GUniFrac; DEGseq; edgeR; vegan; ggplot2
Referenced in: 1 Publication

Referenced by 1 Author

1 Xia, Yinglin

Referenced in 1 Serial

1 ICSA Book Series in Statistics

Referencing Publications by Year