DA.anova: Run 'anova' on all features from 'DAtest' results with...

In Russel88/DAtest: Comparing Differential Abundance/Expression Methods

Run anova on all features from DAtest results with allResults = TRUE

Description

Works on "lrm", "llm", "llm2", "lma", "lmc". Non-paired "neb"

Usage

DA.anova(results, p.adj = "fdr", ...)

Arguments

results	Output from a DA."test" function with allResults = TRUE
p.adj	P-value adjustment method. See p.adjust for details. Default "fdr"
...	Additional arguments for anova function

Value

A data.frame with output from anova and adjusted p.values for each predictor and feature

Examples

# Creating random count_table, predictor, and covariate
set.seed(5)
mat <- matrix(rnbinom(1500, size = 0.5, mu = 500), nrow = 100, ncol = 15)
rownames(mat) <- 1:100
pred <- c(rep("A", 5), rep("B", 5), rep("C", 5))
covar <- rnorm(15)

# Running linear model and then anova on each feature
res <- DA.lmc(mat, pred, covars = list(Something = covar), allResults = TRUE)
res.ano <- DA.anova(res)

Russel88/DAtest documentation built on March 24, 2022, 3:50 p.m.