marker.test: 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
marker.test(object, cells.1, cells.2, genes.use = NULL, thresh.use = log(2))
Arguments
genes.use
Genes to test. Default is to use all genes.
thresh.use
Limit testing to genes which show, on average, at least
X-fold difference (log-scale) between the two groups of cells.Increasing thresh.use speeds up the function, but can miss weaker signals.
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.