IFAA: Robust Analysis for Absolute Abundance in Microbiome

A novel approach to make inference on the association of covariates with the absolute abundance (AA) of 'microbiome' in an ecosystem. It can be also directly applied to relative abundance (RA) data to make inference on AA because the ratio of two RA is equal ratio of their AA. This algorithm can estimate and test the associations of interest while adjusting for potential 'confounders'. The estimates of this method have easy interpretation like a typical regression analysis. High-dimensional covariates are handled with regularization and it is implemented by parallel computing. This algorithm finds optimal reference 'taxa/OTU (Operational Taxonomic Unit)/ASV (Amplicon Sequence Bariant)' and uses permutation to control FDR (False Discovery Rate) as described in Zhigang Li, et al. (2020) <arXiv:1909.10101v3>, Zhigang Li, et al. (2018) <doi:10.1007/s12561-018-9219-2>.

Version: 1.0.0
Depends: R (≥ 3.2.0)
Imports: mathjaxr (≥ 1.0-1), methods (≥ 3.3.0), picasso (≥ 1.2.0), expm (≥ 0.999-3), foreach (≥ 1.4.3), rlecuyer (≥ 0.3-3), Matrix (≥ 1.2-14), HDCI (≥ 1.0-2), parallel (≥ 3.3.0), doParallel (≥ 1.0.11), future (≥ 1.12.0)
Suggests: knitr, rmarkdown
Published: 2020-11-04
Author: Zhigang Li [aut, cre]
Maintainer: Zhigang Li <zhigang.li at ufl.edu>
License: GNU General Public License version 2
URL: https://github.com/gitlzg/IFAA
NeedsCompilation: no
Materials: README NEWS
CRAN checks: IFAA results

Downloads:

Reference manual: IFAA.pdf
Vignettes: IFAA
Package source: IFAA_1.0.0.tar.gz
Windows binaries: r-devel: IFAA_1.0.0.zip, r-release: IFAA_1.0.0.zip, r-oldrel: IFAA_1.0.0.zip
macOS binaries: r-release: IFAA_1.0.0.tgz, r-oldrel: IFAA_1.0.0.tgz

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