marina {diggit} | R Documentation |
This function infers the master regulators for the transition between two phenotypes
marina(x, ...) ## S4 method for signature 'matrix' marina(x, y = NULL, mu = 0, regulon, per = 1000, cores = 1, verbose = TRUE) ## S4 method for signature 'ExpressionSet' marina(x, pheno = "cond", group1, group2 = NULL, mu = 0, regulon, per = 1000, cores = 1, verbose = TRUE) ## S4 method for signature 'diggit' marina(x, pheno, group1, group2 = NULL, mu = 0, regulon = NULL, per = 1000, cores = 1, verbose = TRUE)
x |
Object of class diggit, expressionSet object or numerical matrix containing the test samples |
... |
Additional arguments |
y |
Numerical matrix containing the control samples |
mu |
Number indicating the control mean when |
regulon |
Transcriptional interactome |
per |
Interger indicating the number of permutations to compute the marina null model |
cores |
Integer indicating the number of cores to use (1 for Windows-based systems) |
verbose |
Logical, whether progress should be reported |
pheno |
Character string indicating the phenotype data to use |
group1 |
Vector of character strings indicating the category from phenotype |
group2 |
Vector of character strings indicating the category from phenotype |
Updated diggit object with Master Regulator results
cores <- 3*(Sys.info()[1] != "Windows")+1 data(gbm.expression, package="diggitdata") data(gbm.aracne, package="diggitdata") eset <- exprs(gbmExprs) samples <- pData(gbmExprs)[["subtype"]] x <- eset[, samples=="MES"] y <- eset[, samples=="PN"] dgo <- marina(x, y, regulon=gbmTFregulon, per=100, cores=cores) dgo diggitMR(dgo)[1:5] dgo <- marina(gbmExprs, pheno="subtype", group1="MES", group2="PN", regulon=gbmTFregulon, per=100, cores=cores) dgo diggitMR(dgo)[1:5] x <- diggitClass(expset=gbmExprs, regulon=gbmTFregulon) dgo <- marina(x, pheno="subtype", group1="MES", group2="PN", per=100, cores=cores) dgo diggitMR(dgo)[1:5]