Description Usage Arguments Details Value Examples
View source: R/differential_functions.R
This function performs differential abundance testing between groups of a specified phenotype. Four methods are available: limma, Kruskal-Wallis, ZILN and DESeq2 (see details).
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aggdat |
aggregated MRExperiment |
level |
Feature level. |
phenotype |
Phenotype to test. |
phenolevels |
levels of the phenotype to restrict the comparison to |
log |
Log2 transform data. Default is TRUE. |
coef |
Numeric which indicates which pairwise comparison to analyze
when there are more than two groups. Corresponds to the column number of the
model matrix produced by |
method |
Differential testing method. One of "limma" (default), "Kruskal-Wallis", "ZILN", or "DESeq2". |
limma is a differential expression tool for microarray data using linear models. It can also be applied to microbiome data.
The Kruskal-Wallis test is a non-parametric rank test which examines if groups come from the same distribution. A significant result indicates at least one group is distributionally different than another group.
ZILN is a zero-inflated log-normal model implemented in
fitFeatureModel()
of the metagenomeSeq
package.
DeSeq2 performs differential gene expression analysis based on the negative binomial distribution
data.frame holding results of the differential analysis
1 2 3 4 | data("mouseData", package = "metagenomeSeq")
aggdat <- aggFeatures(mouseData, level = "genus")
runDiffTest(aggdat = aggdat,level = "genus",
phenotype = "diet", method = "Kruskal-Wallis")
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