Description Usage Arguments Details Value Author(s) See Also Examples
View source: R/interventionEffects.R
This function assesses which nodes are downstream of the nodes that are the target of the interventions. The samples are assumed to be independent, and the difference between the inhibited and baseline concentrations is assumed to be Gaussian. This leads to a tdistribution for the mean difference across the timecourse.
1  interventionEffects(d, cellLine, baseline, inhibited)

d 
A microarray spreadsheet, a samples by (4 + P) matrix, where P is the number of measurements for each sample. 
cellLine 
The cell line to investigate (must match an entry in column 1 of 
baseline 
The baseline inhibition condition (must match an entry in column 2 of 
inhibited 
The active inhibition condition (must match an entry in column 2 of 
The function performs a ttest for each stimuli seperately as well as for all the stimuli combined together, which may be less reliable because the assumptions are stronger.
n.differences 
A vector giving the number of differences used to calculate the tstatistic for each stimulus. 
t.statistics 
A vector of tstatistics for the stimuli separately. 
degrees.freedom 
The corresponding vector of degrees of freedom for each test. 
p.values 
The corresponding vector of pvalues. 
heatmap.p.values 
The corresponding vector of sign(T)(1p). This can make a nice heatmap, as significant increases and significant decreases in concentration are at opposite ends of the scale. 
all.stim.t.statistic 
The tstatistic for the stimuli combined. 
all.stim.degrees.freedom 
The degrees of freedom for the stimuli combined. 
all.stim.p.values 
The pvalue for the stimuli combined. 
all.stim.heatmap.p.values 
sign(T)(1p) for all stimuli combined. 
Simon Spencer
formatData
, interventionalDBNpackage
1 2 3 4 5 6 7 8 9 10 11 12 13  data(interventionalData)
effect1<interventionEffects(interventionalData,1,"DMSO","EGFRi")
effect2<interventionEffects(interventionalData,1,"DMSO","AKTi")
heats<rbind(effect1$heatmap.p.values,effect2$heatmap.p.values)
image(heats, breaks=c(1,0.95,0.9,0.9,0.95,1),
col=c("red","darkred","black","darkgreen","green"),xaxt="n",yaxt="n",
xlab="Green = up when inhibitor is present\nRed = down when inhibitor is present")
# Or use the package gplots for more colour graduation
#library("gplots")
#image(heats,breaks=c(1,0.999,0.99,0.975,0.95,0.9,0.9,0.95,0.975,0.99,0.999,1)
# ,col=redgreen(11),xaxt="n",yaxt="n")
axis(1,0:1,c("EGFRi","AKTi"))
axis(2,0:14/14,colnames(effect1$p.values),las=1)

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