interventionEffects: Calculate interventional effects

Description Usage Arguments Details Value Author(s) See Also Examples

View source: R/interventionEffects.R

Description

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 t-distribution for the mean difference across the timecourse.

Usage

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interventionEffects(d, cellLine, baseline, inhibited)

Arguments

d

A microarray spreadsheet, a samples by (4 + P) matrix, where P is the number of measurements for each sample.
Column 1 gives the cell line in each sample.
Column 2 gives the inhibitor used in each sample.
Column 3 gives the stimulus used in each sample.
Column 4 gives the time each sample was measured.

cellLine

The cell line to investigate (must match an entry in column 1 of d). Must be specified even if there is only one.

baseline

The baseline inhibition condition (must match an entry in column 2 of d).

inhibited

The active inhibition condition (must match an entry in column 2 of d).

Details

The function performs a t-test for each stimuli seperately as well as for all the stimuli combined together, which may be less reliable because the assumptions are stronger.

Value

n.differences

A vector giving the number of differences used to calculate the t-statistic for each stimulus.

t.statistics

A vector of t-statistics for the stimuli separately.

degrees.freedom

The corresponding vector of degrees of freedom for each test.

p.values

The corresponding vector of p-values.

heatmap.p.values

The corresponding vector of sign(T)(1-p). 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 t-statistic for the stimuli combined.

all.stim.degrees.freedom

The degrees of freedom for the stimuli combined.

all.stim.p.values

The p-value for the stimuli combined.

all.stim.heatmap.p.values

sign(T)(1-p) for all stimuli combined.

Author(s)

Simon Spencer

See Also

formatData, interventionalDBN-package

Examples

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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)

interventionalDBN documentation built on May 30, 2017, 8:24 a.m.