getDecisions {celda} | R Documentation |
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.
getDecisions(rules, features) getDecisions(rules, features)
rules |
List object. The |
features |
A L (features) by N (samples) numeric matrix. |
A character vector of label predicitions.
A character vector of label predicitions.
## 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)