fCNV {diggit} | R Documentation |
This function infers functional CNVs by computing their association with gene expression
fCNV(x, ...) ## S4 method for signature 'diggit' fCNV(x, expset = NULL, cnv = NULL, method = c("spearman", "mi", "pearson", "kendall"), cores = 1, verbose = TRUE) ## S4 method for signature 'ExpressionSet' fCNV(x, cnv, method = c("spearman", "mi", "pearson", "kendall"), cores = 1, verbose = TRUE) ## S4 method for signature 'matrix' fCNV(x, cnv, method = c("spearman", "mi", "pearson", "kendall"), cores = 1, verbose = TRUE) ## S4 method for signature 'data.frame' fCNV(x, cnv, method = c("spearman", "mi", "pearson", "kendall"), cores = 1, verbose = TRUE)
x |
Object of class diggit, expressionSet object or numeric matrix of expression data, with features in rows and samples in columns |
... |
Additional arguments |
expset |
Optional numeric matrix of expression data |
cnv |
Optional numeric matrix of CNVs |
method |
Character string indicating the method for computing the association between CNVs and expression |
cores |
Integer indicating the number of cores to use (1 for Windows-based systems) |
verbose |
Logical, whether to report analysis progress |
Objet of class diggit with updated fCNV slot
data(gbm.expression, package="diggitdata") data(gbm.cnv, package="diggitdata") genes <- intersect(rownames(gbmExprs), rownames(gbmCNV))[1:100] gbmCNV <- gbmCNV[match(genes, rownames(gbmCNV)), ] dgo <- diggitClass(expset=gbmExprs, cnv=gbmCNV) dgo <- fCNV(dgo) dgo diggitFcnv(dgo)[1:5] dgo <- fCNV(gbmExprs, gbmCNV) print(dgo) diggitFcnv(dgo)[1:5] dgo <- fCNV(exprs(gbmExprs), gbmCNV) dgo diggitFcnv(dgo)[1:5] dgo <- fCNV(as.data.frame(exprs(gbmExprs)), gbmCNV) dgo diggitFcnv(dgo)[1:5]