getDecisions {celda} | R Documentation

## Gets cluster estimates using rules generated by 'celda::findMarkersTree'

### Description

Get decisions for a matrix of features. Estimate cell cluster membership using feature matrix input.

Get decisions for a matrix of features. Estimate cell cluster membership using feature matrix input.

### Usage

    getDecisions(rules, features)

    getDecisions(rules, features)

### Arguments

`rules` | List object. The `rules` element from `findMarkersTree` output. Returns NA if cluster estimation was ambiguous.
`features` | A L (features) by N (samples) numeric matrix.

### Value

A character vector of label predicitions.

A character vector of label predicitions.

### Examples

    ## Not run:
    library(M3DExampleData)
    counts <- M3DExampleData::Mmus_example_list$data
    # Subset 500 genes for fast clustering
    counts <- as.matrix(counts[seq(1501, 2000), ])
    # Cluster genes and samples each into 10 modules
    sce <- celda_CG(counts = counts, L = 10, K = 5, verbose = FALSE)
    # Get features matrix and cluster assignments
    factorized <- factorizeMatrix(sce)
    features <- factorized$proportions$cell
    class <- celdaClusters(sce)
    # Generate Decision Tree
    DecTree <- findMarkersTree(features,
      class,
      oneoffMetric = "modified F1",
      threshold = 1,
      consecutiveOneoff = FALSE)
    # Get sample estimates in training data
    getDecisions(DecTree$rules, features)

    ## End(Not run)

[Package celda version 1.6.1 Index]