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Last data update: 2014.03.03

R: Plot the gene set space

plotGS

R Documentation

Plot the gene set space

Description

Plot the gene set space of objects of "moa" and "mgsa"

Usage

  plotGS(x, axes=1:2, center.only=FALSE, topN=1, data.pch=20, data.col=1, highlight.col = 2,
         label=NULL, label.cex=1, layout=NULL, ...)

Arguments

`x`	An object of class `mgsa-class` or `moa.sup-class`
`axes`	An integer vector in the length 2 to indicate the axes to be drawn.
`center.only`	A logical to indicate whether the separate gene set spaces from each of the data set should be plotted. Default is FALSE.
`topN`	An integer specify N gene set from the most positive and negative end of axes to be labeled
`data.pch`	The shape for plotting each data set. This argument is passed to points function, so only used when separate gene set spaces are plotted (i.e. center.only = FALSE).
`data.col`	The col for plotting each data set. This argument is passed to points function, so only used when separate gene set spaces are plotted (i.e. center.only = FALSE).
`highlight.col`	The color used to highlight the selected gene sets
`label`	Either a character vector or NULL (default). The character vector should be the name of some gene sets want ot be labeled.
`label.cex`	Passed to `text` function to adjust the the labels
`layout`	A matrix passed to the `layout` function.
`...`	Other arguments passed to `points`

Details

This is a convenience function to explore the gene set space so not very flexible. For customized plot, please use the object of data@coord.comb and data@coord.sep.

Value

If assign to variable, A list of selected/highlighted gene set at the (positve and negative) end of each axis will be returned.

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)

  plotGS(mgsa, center.only = TRUE, topN=5)
  res <- plotGS(mgsa, center.only = FALSE, data.pch=1:4, data.col=1:4)
  res

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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Type 'demo()' for some demos, 'help()' for on-line help, or
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> library(mogsa)
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/mogsa/plotGS.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plotGS
> ### Title: Plot the gene set space
> ### Aliases: plotGS
> 
> ### ** 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)
> 
>   plotGS(mgsa, center.only = TRUE, topN=5)
>   res <- plotGS(mgsa, center.only = FALSE, data.pch=1:4, data.col=1:4)
>   res
$agilent
$agilent$ax1.negN
[1] "INTEGRAL_TO_MEMBRANE"

$agilent$ax1.posN
[1] "MARTENS_TRETINOIN_RESPONSE_DN"

$agilent$ax2.negN
[1] "ACEVEDO_METHYLATED_IN_LIVER_CANCER_DN"

$agilent$ax2.posN
[1] "CACGTG_V$MYC_Q2"


$hgu133
$hgu133$ax1.negN
[1] "CHARAFE_BREAST_CANCER_LUMINAL_VS_MESENCHYMAL_DN"

$hgu133$ax1.posN
[1] "PUJANA_ATM_PCC_NETWORK"

$hgu133$ax2.negN
[1] "MEISSNER_BRAIN_HCP_WITH_H3K4ME3_AND_H3K27ME3"

$hgu133$ax2.posN
[1] "RUTELLA_RESPONSE_TO_HGF_UP"


$hgu133p2
$hgu133p2$ax1.negN
[1] "CHARAFE_BREAST_CANCER_LUMINAL_VS_MESENCHYMAL_DN"

$hgu133p2$ax1.posN
[1] "MARSON_BOUND_BY_FOXP3_UNSTIMULATED"

$hgu133p2$ax2.negN
[1] "PROTEIN_METABOLIC_PROCESS"

$hgu133p2$ax2.posN
[1] "KRIGE_RESPONSE_TO_TOSEDOSTAT_24HR_DN"


$hgu95
$hgu95$ax1.negN
[1] "REN_ALVEOLAR_RHABDOMYOSARCOMA_DN"

$hgu95$ax1.posN
[1] "PUJANA_ATM_PCC_NETWORK"

$hgu95$ax2.negN
[1] "KOINUMA_TARGETS_OF_SMAD2_OR_SMAD3"

$hgu95$ax2.posN
[1] "MODULE_137"


> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>