Object Oriented Microarray Library: Two-Group Statistics

The two-group statistics module provides the definition of the two.group.statistics class. See the bottom of the page for an example of how the class can be used.

Attributes

n1

An integer, the number of items in the first group.

mean1

The gene-by-gene vector of means for the first group.

var1

The gene-by-gene vector of variances for the first group.

n2

An integer, the number of items in the second group.

mean2

The gene-by-gene vector of means for the second group.

var2

The gene-by-gene vector of variances for the second group.

overall.mean

The gene-by-gene vector of means for the combined groups.

overall.var

The gene-by-gene vector of variances for the combined groups.

pooled.var

The gene-by-gene vector of variances for the combined groups combined by pooling the estimates for the two groups, using the standard formulas from, for example, the t-test.

Methods

two.group.stats(data, split)

Constructor. The required arguments are a data frame, data, and a logical vector, split, which is used to classify the columns of the data frame into two groups.

summary(object, ...)

Write out a summary of the object.

print(object, ...)

Print all the information in the object.

plot(object, name, aname, bname, ...)

This method produces six different plots of the object. Only the object argument is required. The optional aname, bname, and name arguments are usd as title for the first three plots, respectively. The plots are:

1. A plot of the vector of standard deviations from the first group as a function of the means.
2. The same thing for the second group.
3. The same thing for the combined groups.
4. A plot of the difference in means as a function of the overall means, along with a loess fit.
5. A plot of the difference in means as a function of position, together with a loess fit.
6. A comparison of the overall mean with the pooled mean.

as.data.frame(object)

Convert the object to a data frame, which contains all the information except the values n1 andn2.

Description

An object of the two.group.stats class is constructed from a data frame containing N rows (genes) and P columns (samples), along with a logical vector of length P that separates the samples into two groups. On a gene-by-gene basis, we compute the mean and variance, along with the pooled variance for combining the two groups.

  bogus <- matrix(rnorm(30*1000, 8, 3), ncol=30, nrow=1000)
  splitter <- rep(F, 30)
  splitter[16:30] <- T

  x <- two.group.stats(bogus, splitter)
  summary(x)

  opar<-par(mfrow=c(2,3), pch='.')
  plot(x)
  par(opar)