discretize_exprs_supervised {FCBF} | R Documentation |
Uses several discretizations and selects the one that is best for a given variable (gene) in comparison to a target class by equivocation
discretize_exprs_supervised(expression_table, target, parallel = FALSE)
expression_table |
A previously normalized expression table |
target |
A series of labels matching each of the values in the gene vector (genes in rows, cells/samples in columns) |
parallel |
Set calculations in parallel. May be worth it if the number of rows and columns is really large. Do watchout for memory overload. |
A data frame with the discretized features in the same order as previously
data(scDengue) exprs <- as.data.frame(SummarizedExperiment::assay(scDengue, 'logcounts')) exprs <- exprs [1:200, 1:120] infection <- SummarizedExperiment::colData(scDengue) target <- infection$infection discrete_expression <- as.data.frame(discretize_exprs_supervised(exprs,target)) fcbf(discrete_expression,target, thresh = 0.05, verbose = TRUE)