plot.bayesian {sma}R Documentation

Plots an Odds Ratio of Each Gene in a Multi-slide microarray Experiment

Description

This function takes the normalized expression estimates from a multi-slide microarray experiment (M-values output by stat.ma) and plots an odds ratio for each gene: log( Pr(the gene is differentially expressed) / Pr(the gene is not differentially expressed) ) vs the gene-specific average M-value. Alternatively, the output of stat.bayesian() can be given as input. The resulting plot is the same, but tedious calculations don't have to be done all over again.

Usage

plot.bayesian(X=NULL, nb=NULL, nw=1, lods=NULL, Xprep=NULL, para=list(p
= 0.01, v = NULL, a = NULL, c = NULL, k = NULL))

Arguments

X List containing matrix of (normalized) log expression ratios M = log_2 (R/G) (E.g. output from stat.ma())
nb Number of slides containing spots for a gene (common for all genes). Unnecessary argument if nw=1.
nw Number of spots for a gene within each slide (common to all genes).Default is 1.
lods The log odds ratio for each gene. Not necessary input. See details!
Xprep Some data structures useful in this graphical presentation. Not necessary input. See details!
para Estimates of the parameters used in the Bayesian calculations. Not necessary input. See details!

Author(s)

Ingrid Lönnstedt ingrid@math.uu.se
Yee Hwa Yang, yeehwa@stat.berkeley.edu

See Also

stat.bayesian

Examples

data(MouseArray)
## mouse.setup <- init.grid() 
## mouse.data <- init.data() ## see \emph{init.data} 
## mouse.lratio <- stat.ma(mouse.data, mouse.setup)

#Alternative 1
## mouse.bayesian<-stat.bayesian(X=mouse.lratio)
## plot.bayesian(Xprep=mouse.bayesian$Xprep, lods=mouse.bayesian$lods)

#Alternative 2
## plot.bayesian(X=mouse.lratio)

#My changes
## my.para<-mouse.bayesian$para
## my.para$p<-0.005
## plot.bayesian(Xprep=mouse.bayesian$Xprep, para=my.para)