Package 'limma' - Bioconductor

12 08.Tests
07.SingleChannel
Topic: Individual Channel Analysis of Two-Color Microarrays
Description
This page gives an overview of the LIMMA functions fit linear models to two-color microarray data
in terms of the log-intensities rather than log-ratios.
The function intraspotCorrelation estimates the intra-spot correlation between the two channels.
The regression function lmscFit takes the correlation as an argument and fits linear models to
the two-color data in terms of the individual log-intensities. The output of lmscFit is an MArrayLM
object just the same as from lmFit, so inference proceeds in the same way as for log-ratios once
the linear model is fitted. See 06.LinearModels.
The function targetsA2C converts two-color format target data frames to single channel format, i.e,
converts from array-per-line to channel-per-line, to facilitate the formulation of the design matrix.
Author(s)
Gordon Smyth
08.Tests
Topic: Hypothesis Testing for Linear Models
Description
LIMMA provides a number of functions for multiple testing across both contrasts and genes. The
starting point is an MArrayLM object, called fit say, resulting from fitting a linear model and running
eBayes and, optionally, contrasts.fit. See 06.LinearModels or 07.SingleChannel for details.
Multiple testing across genes and contrasts
The key function is decideTests. This function writes an object of class TestResults, which is
basically a matrix of -1, 0 or 1 elements, of the same dimension as fit$coefficients, indicating
whether each coefficient is significantly different from zero. A number of different multiple testing
strategies are provided. The function calls other functions classifyTestsF, classifyTestsP and
classifyTestsT which implement particular strategies. The function FStat provides an alternative
interface to classifyTestsF to extract only the overall moderated F-statistic.
selectModel chooses between linear models for each probe using AIC or BIC criteria. This is an
alternative to hypothesis testing and can choose between non-nested models.
A number of other functions are provided to display the results of decideTests. The functions
heatDiagram (or the older version heatdiagram displays the results in a heat-map style display.
This allows visual comparison of the results across many different conditions in the linear model.
The functions vennCounts and vennDiagram provide Venn diagram style summaries of the results.
Summary and show method exists for objects of class TestResults.
The results from decideTests can also be included when the results of a linear model fit are written
to a file using write.fit.