find_biomarker {animalcules} | R Documentation

## Identify biomarkers

### Description

Identify biomarkers

### Usage

    find_biomarker(
      MAE,
      tax_level,
      input_select_target_biomarker,
      nfolds = 3,
      nrepeats = 3,
      seed = 99,
      percent_top_biomarker = 0.2,
      model_name = c("logistic regression", "random forest")
    )

### Arguments

`MAE` | A multi-assay experiment object
`tax_level` | The taxon level used for organisms
`input_select_target_biomarker` | Which condition is the target condition
`nfolds` | number of splits in CV
`nrepeats` | number of CVs with different random splits
`seed` | for repeatable research
`percent_top_biomarker` | Top importance percentage to pick biomarker
`model_name` | one of 'logistic regression', 'random forest'

### Value

A list

### Examples

    data_dir = system.file('extdata/MAE.rds', package = 'animalcules')
    toy_data <- readRDS(data_dir)
    p <- find_biomarker(toy_data,
                        tax_level='family',
                        input_select_target_biomarker=c('DISEASE'),
                        nfolds = 3,
                        nrepeats = 3,
                        seed = 99,
                        percent_top_biomarker = 0.2,
                        model_name = 'logistic regression')
    p

[Package animalcules version 1.8.1 Index]