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Method for determining confidence in specific bifurcations in the cluster tree. Use the Out of Bag (OOB) error of a random forest classifier to judge confidence.
AssessSplit(object, node, cluster1, cluster2, print.output = TRUE, ...)
Seurat object
Node in the cluster tree in question
First cluster to compare
Second cluster to compare
Print the OOB error for the classifier
Arguments passed on to BuildRFClassifier
Vector of genes to build the classifier on
Vector of classes to build the classifier on
Additional progress print statements
Returns the Out of Bag error for a random forest classifier trained on the split from the given node
# NOT RUN {
pbmc_small
pbmc_small <- FindClusters(object = pbmc_small, reduction.type = "pca",
dims.use = 1:10, resolution = 1.1, save.SNN = TRUE)
pbmc_small <- BuildClusterTree(pbmc_small, reorder.numeric = TRUE, do.reorder = TRUE)
# Assess based on a given node
AssessSplit(pbmc_small, node = 11)
# Asses based on two given clusters (or vectors of clusters)
AssessSplit(pbmc_small, cluster1 = 5, cluster2 = 6)
AssessSplit(pbmc_small, cluster1 = 4, cluster2 = c(5, 6))
# }
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