Calculate median values of markers for each cluster

Calculate median value of each marker in each cluster.

Usage

medianByClusterMarker(
  SE,
  assay = 1,
  marker_in_column = TRUE,
  column_cluster = "cluster_id",
  use_marker = NULL
)

Arguments

SE

A SummarizedExperiment object.

assay

A numeric index or assay name indicating with assay of SE to use to calculate medians.

marker_in_column

A logical scalar, indicating whether markers (genes, features) are in the columns of SE or not.

column_cluster

The name of the column of colData(SE) that contains the cluster assignment of each sample.

use_marker

A logical or numeric vector such that SE[use_marker, ] (if marker_in_column = FALSE) or SE[, use_marker] (if marker_in_column = TRUE) subsets SE to the markers that should be retained. If NULL (default), all markers are used.

Value

A SummarizedExperiment object containing the median value of each marker in each cluster.

Author

Ruizhu Huang, Charlotte Soneson

Examples

suppressPackageStartupMessages({
    library(SummarizedExperiment)
})

## Simulate data with 100 cells and 10 markers (5 type, 5 state markers)
set.seed(1)
count <- matrix(rpois(n = 1000, lambda = 10), nrow = 100)
colnames(count) <- paste0("mk", 1:10)
rowD <- data.frame("cluster" = sample(seq_len(6), 100, replace = TRUE))
colD <- data.frame(type_marker = rep(c(FALSE, TRUE), each = 5))

## SE with markers in columns
d_se <- SummarizedExperiment(assays = list(counts = count),
                             rowData = rowD,
                             colData = colD)
medianByClusterMarker(SE = d_se, marker_in_column = TRUE,
                      column_cluster = "cluster",
                      use_marker = colData(d_se)$type_marker)
#> class: SummarizedExperiment 
#> dim: 6 5 
#> metadata(0):
#> assays(1): counts
#> rownames(6): 1 2 ... 5 6
#> rowData names(1): cluster
#> colnames(5): mk6 mk7 mk8 mk9 mk10
#> colData names(0):

## SE with markers in rows
d_se <- SummarizedExperiment(assays = list(counts = t(count)),
                             rowData = colD,
                             colData = rowD)
medianByClusterMarker(SE = d_se, marker_in_column = FALSE,
                      column_cluster = "cluster",
                      use_marker = rowData(d_se)$type_marker)
#> class: SummarizedExperiment 
#> dim: 5 6 
#> metadata(0):
#> assays(1): counts
#> rownames(5): mk6 mk7 mk8 mk9 mk10
#> rowData names(0):
#> colnames(6): 1 2 ... 5 6
#> colData names(1): cluster