plotVar: Plot variable (gene) spaces of result from MCIA or CIA

In mengchen18/omicade4: Multiple co-inertia analysis of omics datasets

Description

The user level function for plotting variable space of mcia or cia, which could be used to visualize selected variables (genes) across datasets. It calls plotVar.cia or plotVar.mcia.

Usage

  plotVar(x, var = NA, axes = 1:2, 
          var.col = "red", var.lab = FALSE, bg.var.col = "gray", 
          nlab = 0, sepID.data=NULL, sepID.sep="_", ...)

Arguments

x	An object of class cia or mcia
var	A character vector defining the variables (genes) are going to be labelled and coloured. The default NA means no variables (genes) selected.
axes	An integer vector in length 2 indicating which axes are going to be plotted. Default are the first two axes.
var.col	The colour of selected variables (genes), the length of this argument should be either 1 (uniform colour) or the length of var (each var has a specified colour).
var.lab	A logical indicating if the variables (genes) selected should be labelled, the default is FALSE
bg.var.col	Colour code for unselected variables (genes) in all datasets.
nlab	An integer indicating how many top weighted genes on each axis should be labelled.
sepID.data	This argument enables a more generalized mapping of identifiers in different datasets. For example, if there is a PTM (post-transcriptional modification) dataset in one of the data.frames, the corresponding protein could be detected with setting this argument. For more details, see "details" section.
sepID.sep	Used to help determine the separator of variables (genes) in the sepID.data. For more details, see "details" section.
...	Other arguments

Details

For the sepID.data, a typical example is the post-transcriptional modification (PTM) data. The name of variables (genes) have a general form like "proteinName_modificationSite". The sepID.data specifies the IDs from dataset that should be separated, sepID.sep specifies the separator of protein name and modification site. This is used to determine the same proteins/genes across different datasets.

Value

If var is not NA, a data frame is returned, with rows for variables (genes) of interest and columns of logical values indicating which dataset contains which variables (genes).

Author(s)

Chen Meng

See Also

See Also as plotVar.cia, plotVar.mcia

Examples

data(NCI60_4arrays)
mcoin <- mcia(NCI60_4arrays)
plotVar(mcoin, var=c("S100B", "S100A1"), var.lab=TRUE)

# an example for the usage of sepID.data and sepID.sep
nci60_mod <- NCI60_4arrays
rownames(nci60_mod$hgu95) <- paste(rownames(nci60_mod$hgu95), "s1", sep="_")
mcoin_mod <- mcia(nci60_mod)
id <- split(rownames(mcoin_mod$mcoa$Tco), mcoin_mod$mcoa$TC$T)
sapply(id, function(x) head(x))


plotVar(mcoin_mod, var=c("S100B", "S100A1"), var.lab=TRUE, sepID.data=1:4, sepID.sep = c("\\.", "\\.", "\\.", "_"))
plotVar(mcoin_mod, var=c("S100B", "S100A1"), var.lab=TRUE, sepID.data=4, sepID.sep="_")
plotVar(mcoin_mod, var=c("S100B", "S100A1"), var.lab=TRUE, sepID.data=1:3, sepID.sep="\\.")

mengchen18/omicade4 documentation built on Nov. 2, 2020, 10:30 a.m.