TF-IDF

Run tf-idf on a metadata table.

tfidf(
  clusts,
  label_var = "dataset",
  cluster_var = "seurat_clusters",
  terms_per_cluster = 1,
  replace_regex = "[.]|[_]|[-]",
  force_new = FALSE,
  with_ties = FALSE
)

Arguments

clusts

data.frame/data.table with the per-cell metadata and cluster assignments.

label_var

Which cell metadata column to input to NLP analysis.

cluster_var

Which cell metadata column to use to identify which cluster each cell is assigned to.

terms_per_cluster

The maximum number of words to return per cluster.

replace_regex

Characters used to split label_var into terms (i.e. tokens) for NLP enrichment analysis.

force_new

If NLP results are already detected the metadata, set force_new=TRUE to replace them with new results.

with_ties

Should ties be kept together? The default, TRUE, may return more rows than you request. Use FALSE to ignore ties, and return the first n rows.

Value

A data.frame with TF-IDF enrichment results per cluster, including columns: cluster, word, n, total, samples, tf, idf, tf_idf.

Examples

data("pseudo_seurat")
clusts <- pseudo_seurat[[]]
clusts$cluster <- clusts$seurat_clusters
tfidf_results <- tfidf(clusts = clusts,
                       label_var = "celltype",
                       cluster_var = "cluster")