getDecisions: Gets cluster estimates using rules generated by...

Description Usage Arguments Value Examples

View source: R/getDecisions.R View source: R/findMarkersTree.R

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

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getDecisions(rules, features)

getDecisions(rules, features)

Arguments

rules

List object. The 'rules' element from 'findMarkers' 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

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

# Get sample estimates in training data
getDecisions(DecTree$rules, features)

## End(Not run)

celda documentation built on June 9, 2020, 2 a.m.