Seurat (version 2.3.4)

MarkerTest: ROC-based marker discovery

Description

Identifies 'markers' of gene expression using ROC analysis. For each gene, evaluates (using AUC) a classifier built on that gene alone, to classify between two groups of cells.

Usage

MarkerTest(object, cells.1, cells.2, genes.use = NULL, print.bar = TRUE,
  assay.type = "RNA")

Arguments

object

Seurat object

cells.1

Group 1 cells

cells.2

Group 2 cells

genes.use

Genes to test. Default is to use all genes

print.bar

Print a progress bar once expression testing begins (uses pbapply to do this)

assay.type

Type of assay to fetch data for (default is RNA)

Value

Returns a 'predictive power' (abs(AUC-0.5)) ranked matrix of putative differentially expressed genes.

Details

An AUC value of 1 means that expression values for this gene alone can perfectly classify the two groupings (i.e. Each of the cells in cells.1 exhibit a higher level than each of the cells in cells.2). An AUC value of 0 also means there is perfect classification, but in the other direction. A value of 0.5 implies that the gene has no predictive power to classify the two groups.

Examples

# NOT RUN {
pbmc_small
MarkerTest(pbmc_small, cells.1 = WhichCells(object = pbmc_small, ident = 1),
            cells.2 = WhichCells(object = pbmc_small, ident = 2))

# }