box.gs.feature: boxplot of gene set variables across all samples.

In mogsa: Multiple omics data integrative clustering and gene set analysis

Description

boxplot to show the variables (e.g. gene expression) of a gene set across all samples.

Usage

  box.gs.feature(x, gs, moa = NULL, col = 1, layout = NULL, plot = TRUE, obs.order = NULL, ...)

Arguments

x	An object of calss mgsa-class or moa.sup-class
gs	Gene set want to be explored
moa	An obejct of class moa. It is required if x is an object of class moa.sup-class
col	The coler code for samples
layout	The layout control, see examples.
plot	A logical indicates whether the result should be ploted. If FALSE, a list of expression matrix of the gene set genes is returned. Otherwise nothing returned.
obs.order	Can be used to reorder the martrix, could be used when clustering result is available.
...	The arguments passed to boxplot

Details

This is a convenient function used to explore the expression of a set of features/genes

Value

Do not return anything (plot=TRUE) or return a list of matrix (plot=FALSE) depends on plot arugment.

Author(s)

Chen meng

Examples

  # library(mogsa)
  # loading gene expression data and supplementary data
  data(NCI60_4array_supdata)
  data(NCI60_4arrays)
  mgsa <- mogsa(x = NCI60_4arrays, sup=NCI60_4array_supdata, nf=9,
                proc.row = "center_ssq1", w.data = "inertia", statis = TRUE)

  allgs <- colnames(NCI60_4array_supdata[[1]])
  colcode <- as.factor(sapply(strsplit(colnames(NCI60_4arrays$agilent), split="\\."), "[", 1))
  a <- box.gs.feature(x=mgsa, gs=allgs[5], type=3, col=colcode, plot=FALSE)
  box.gs.feature(x=mgsa, gs=allgs[5], type=3, col=colcode, plot=TRUE, layout=matrix(1:4, 2, 2))

mogsa documentation built on Nov. 8, 2020, 5:41 p.m.