Average expression values per cluster

Usage

average_clusters(
  mat,
  metadata,
  cluster_col = "cluster",
  if_log = TRUE,
  cell_col = NULL,
  low_threshold = 0,
  method = "mean",
  output_log = TRUE,
  subclusterpower = 0,
  cut_n = NULL
)

Arguments

mat: expression matrix
metadata: data.frame or vector containing cluster assignments per cell. Order must match column order in supplied matrix. If a data.frame provide the cluster_col parameters.
cluster_col: column in metadata with cluster number
if_log: input data is natural log, averaging will be done on unlogged data
cell_col: if provided, will reorder matrix first
low_threshold: option to remove clusters with too few cells
method: whether to take mean (default), median, 10% truncated mean, or trimean, max, min
output_log: whether to report log results
subclusterpower: whether to get multiple averages per original cluster
cut_n: set on a limit of genes as expressed, lower ranked genes are set to 0, considered unexpressed

Value

average expression matrix, with genes for row names, and clusters for column names

Examples

mat <- average_clusters(
    mat = pbmc_matrix_small,
    metadata = pbmc_meta,
    cluster_col = "classified",
    if_log = FALSE
)
mat[1:3, 1:3]
#>        Naive CD4 T Memory CD4 T CD14+ Mono
#> PPBP    0.01892718   0.02607889 0.08947514
#> LYZ     0.65070360   0.67842980 1.80412017
#> S100A9  0.22047491   0.26729285 1.71088164