samr.plot: Make Q-Q plot for SAM analysis
In samr: SAM: Significance Analysis of Microarrays

Description Usage Arguments Details Author(s) References Examples

Makes the Q-Q plot for a SAM analysis

1	samr.plot(samr.obj, del, min.foldchange=0)

`samr.obj`	Object returned from call to samr
`del`	Value of delta to use. Delta is the vertical distance from the 45 degree line to the upper and lower parallel lines that define the SAM threshold rule.
`min.foldchange`	The minimum fold change desired; should be >1; default is zero, meaning no fold change criterion is applied

Creates the Q-Q plot fro a SAm analysis, marking features (genes) that are significant, ie. lie outside a slab around teh 45 degreee line of width delta. A gene must also pass the min.foldchange criterion to be called significant, if this criterion is specified in the call.

Jun Li and Balasubrimanian Narasimhan and Robert Tibshirani

Tusher, V., Tibshirani, R. and Chu, G. (2001): Significance analysis of microarrays applied to the ionizing radiation response" PNAS 2001 98: 5116-5121, (Apr 24). http://www-stat.stanford.edu/~tibs/sam

#generate some example data
set.seed(100)
x<-matrix(rnorm(1000*20),ncol=20)
dd<-sample(1:1000,size=100)

u<-matrix(2*rnorm(100),ncol=10,nrow=100)
x[dd,11:20]<-x[dd,11:20]+u

y<-c(rep(1,10),rep(2,10))

data=list(x=x,y=y, geneid=as.character(1:nrow(x)),
genenames=paste("g",as.character(1:nrow(x)),sep=""), logged2=TRUE)


samr.obj<-samr(data,  resp.type="Two class unpaired", nperms=50)


samr.plot(samr.obj, del=.3)

Loading required package: impute
Loading required package: matrixStats
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