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Last data update: 2014.03.03

R: plot.oncoscore.timeseries

plot.oncoscore.timeseries

R Documentation

plot.oncoscore.timeseries

Description

plot the OncoScore for a list of genes

Usage

## S3 method for class 'oncoscore.timeseries'
plot(x, gene.number = 5, incremental = FALSE,
  relative = FALSE, main = "OncoScore", xlab = "timepoints",
  ylab = "score", legend.pos = "top", file = NA, ...)

Arguments

`x`	input data as result of the function compute.OncoScore
`gene.number`	number of genes to print
`incremental`	display the OncoScore increment
`relative`	dispaly the incrementa as relative value
`main`	the title
`xlab`	description of x asix (defaul score)
`ylab`	description of y asix (defaul genes)
`legend.pos`	Position of the legend
`file`	where to save the plot
`...`	additional parameter to pass to the lines function

Value

A plot

Examples

data(query.timepoints)
result = compute.oncoscore.timeseries(query.timepoints)
plot.oncoscore.timeseries(result)

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)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(OncoScore)
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/OncoScore/plot.oncoscore.timeseries.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plot.oncoscore.timeseries
> ### Title: plot.oncoscore.timeseries
> ### Aliases: plot.oncoscore.timeseries
> 
> ### ** Examples
> 
> data(query.timepoints)
> result = compute.oncoscore.timeseries(query.timepoints)
### Computing oncoscore for timepoint 2012/03/01 
### Processing data
### Computing frequencies scores 
### Estimating oncogenes
### Results:
	 ASXL1 -> 77.19348 
	 IDH1 -> 74.24489 
	 IDH2 -> 64.1649 
	 SETBP1 -> 34.9485 
	 TET2 -> 74.90108 
### Computing oncoscore for timepoint 2013/03/01 
### Processing data
### Computing frequencies scores 
### Estimating oncogenes
### Results:
	 ASXL1 -> 76.31902 
	 IDH1 -> 78.71551 
	 IDH2 -> 69.99559 
	 SETBP1 -> 46.4559 
	 TET2 -> 73.89695 
### Computing oncoscore for timepoint 2014/03/01 
### Processing data
### Computing frequencies scores 
### Estimating oncogenes
### Results:
	 ASXL1 -> 77.39202 
	 IDH1 -> 81.07946 
	 IDH2 -> 73.46995 
	 SETBP1 -> 64.97398 
	 TET2 -> 70.44331 
### Computing oncoscore for timepoint 2015/03/01 
### Processing data
### Computing frequencies scores 
### Estimating oncogenes
### Results:
	 ASXL1 -> 77.49295 
	 IDH1 -> 82.55032 
	 IDH2 -> 75.58179 
	 SETBP1 -> 63.80208 
	 TET2 -> 69.91466 
### Computing oncoscore for timepoint 2016/03/01 
### Processing data
### Computing frequencies scores 
### Estimating oncogenes
### Results:
	 ASXL1 -> 77.8392 
	 IDH1 -> 83.11346 
	 IDH2 -> 76.75356 
	 SETBP1 -> 65.556 
	 TET2 -> 69.81125 
> plot.oncoscore.timeseries(result)
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> dev.off()
null device 
          1 
>