aIc: Testing for Compositional Pathologies in Datasets

A set of tests for compositional pathologies. Tests for coherence of correlations with aIc.coherent() as suggested by (Erb et al. (2020) <doi:10.1016/j.acags.2020.100026>), compositional dominance of distance with aIc.dominant(), compositional perturbation invariance with aIc.perturb() as suggested by (Aitchison (1992) <doi:10.1007/BF00891269>) and singularity of the covariation matrix with aIc.singular(). Currently tests five data transformations: prop, clr, TMM, TMMwsp, and RLE from the R packages 'ALDEx2', 'edgeR' and 'DESeq2' (Fernandes et al (2014) <doi:10.1186/2049-2618-2-15>, Anders et al. (2013)<doi:10.1038/nprot.2013.099>).

Package details

AuthorGreg Gloor
MaintainerGreg Gloor <ggloor@uwo.ca>
LicenseGPL (>= 3)
Version1.0
URL https://github.com/ggloor/aIc
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("aIc")

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aIc documentation built on Oct. 5, 2022, 1:08 a.m.