differential_abundance {animalcules} | R Documentation

## Differential abundance analysis

### Description

Differential abundance analysis

### Usage

    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"
    )

### Arguments

`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

### Value

A output dataframe

### Examples

    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")

[Package animalcules version 1.3.6 Index]