differential_abundance: Differential abundance analysis
In animalcules: Interactive microbiome analysis toolkit

Description Usage Arguments Value Examples

Differential abundance analysis

differential_abundance(
  MAE,
  tax_level,
  input_da_condition = c(),
  input_da_condition_covariate = NULL,
  min_num_filter = 5,
  input_da_padj_cutoff = 0.05,
  method = "DESeq2"
)

`MAE`	A multi-assay experiment object
`tax_level`	The taxon level used for organisms
`input_da_condition`	Which condition is the target condition
`input_da_condition_covariate`	Covariates added to linear function
`min_num_filter`	Minimum number reads mapped to this microbe
`input_da_padj_cutoff`	adjusted pValue cutoff
`method`	choose between DESeq2 and limma

A output dataframe

data_dir = system.file("extdata/MAE.rds", package = "animalcules")
toy_data <- readRDS(data_dir)
differential_abundance(toy_data,
tax_level="phylum",
input_da_condition=c("DISEASE"),
min_num_filter = 2,
input_da_padj_cutoff = 0.5,
method = "DESeq2")