test_to_known_factors-HierarchicalPartition-method {cola} | R Documentation

## Test correspondance between predicted classes and known factors

### Description

Test correspondance between predicted classes and known factors

### Usage

    ## S4 method for signature 'HierarchicalPartition'
    test_to_known_factors(object, known = get_anno(object[1]),
        depth = 2:max_depth(object), verbose = FALSE)

### Arguments

`object` | A `HierarchicalPartition-class` object.
`depth` | Depth of the hierarchy.
`known` | A vector or a data frame with known factors. By default it is the annotation table set in `hierarchical_partition`.
`verbose` | Whether to print messages.

### Value

A data frame with columns:

- number of samples

- p-values from the tests

- number of classes

The classifications are extracted for each depth.

### Author(s)

Zuguang Gu <z.gu@dkfz.de>

### Examples

    data(golub_cola_rh)
    # golub_cola_rh already has known annotations, so test_to_known_factors()
    # can be directly applied
    test_to_known_factors(golub_cola_rh)

[Package cola version 1.6.0 Index]