# Functions to handle cDNA microarray data, including several methods of data analysis

## Documentation for package ‘maigesPack’ version 1.26.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

A B C D G H I K L M N P R S T misc

## -- A --

activeMod | Functional classification of gene groups
activeModScoreHTML | Save HTML file with global gene scores from functional gene groups classification
activeNet | Functional classification of gene networks
activeNetScoreHTML | Save HTML file with scores and p-values from functional gene networks classification
addGeneGrps | Function to load gene groups into maigesPreRaw object
addPaths | Function to load gene pathways into maigesPreRaw object
as | Coerce a maiges object to classes defined by packages limma and marray
as-method | Coerce a maiges object to classes defined by packages limma and marray

## -- B --

bootstrapCor | Calculate bootstrap p-values for correlation measures
bootstrapMI | Calculate bootstrap p-values for mutual information (MI) measures
bootstrapT | Calculate bootstrap p-values for t statistics
boxplot | Method boxplot for objects defined in this package
boxplot.maiges | Method boxplot for objects defined in this package
boxplot.maigesANOVA | Method boxplot for objects defined in this package
boxplot.maigesDEcluster | Method boxplot for objects defined in this package
boxplot.maigesRaw | Method boxplot for objects defined in this package

## -- C --

calcA | Method calcA to calculate A values
calcA.default | Method calcA to calculate A values
calcA.maigesRaw | Method calcA to calculate A values
calcW | Method calcW to calculate W values
calcW.default | Method calcW to calculate W values
calcW.maigesRaw | Method calcW to calculate W values
classifyKNN | Function to do discrimination analysis
classifyKNNsc | Function to do discrimination analysis, by the search and choose method
classifyLDA | Function to do discrimination analysis
classifyLDAsc | Function to do discrimination analysis, by the search and choose method
classifySVM | Function to do discrimination analysis
classifySVMsc | Function to do discrimination analysis, by the search and choose method
coerce-method | Coerce a maiges object to classes defined by packages limma and marray
compCorr | Compute correlation differences and their p-values
contrastsFitM | Compute Contrasts from Linear Model Fit
createMaigesRaw | Function to create objects of class maigesRaw
createTDMS | Create a tab delimited file for TIGR MeV

## -- D --

deGenes2by2BootT | Function to do differential expression analysis, comparing only two samples
deGenes2by2Ttest | Function to do differential expression analysis, comparing only two samples
deGenes2by2Wilcox | Function to do differential expression analysis, comparing only two samples
deGenesANOVA | Function to do differential expression analysis, using ANOVA models
designANOVA | Function to construct design an contrasts matrices for ANOVA models
dim.maiges | Retrieve the dimension of microarray objects
dim.maigesANOVA | Retrieve the dimension of microarray objects
dim.maigesPreRaw | Retrieve the dimension of microarray objects
dim.maigesRaw | Retrieve the dimension of microarray objects

## -- G --

gastro | Gastro-esophagic dataset
gastro.norm | Gastro-esophagic dataset
gastro.raw | Gastro-esophagic dataset
gastro.raw2 | Gastro-esophagic dataset
gastro.summ | Gastro-esophagic dataset
getLabels | Method getLabels to pick gene and sample labels
getLabels.default | Method getLabels to pick gene and sample labels
getLabels.maigesDE | Method getLabels to pick gene and sample labels
getLabels.maigesDEcluster | Method getLabels to pick gene and sample labels
getLabels.MAList | Method getLabels to pick gene and sample labels
getLabels.marrayNorm | Method getLabels to pick gene and sample labels
getLabels.marrayRaw | Method getLabels to pick gene and sample labels
getLabels.RGList | Method getLabels to pick gene and sample labels

## -- H --

heatmapsM | Function to plot heatmaps separating groups generated by SOM or k-means
hierM | Function to do hierarchical cluster analysis
hierMde | Function to do hierarchical cluster analysis

## -- I --

image | Method image for objects defined in this package
image.maiges | Method image for objects defined in this package
image.maigesActMod | Method image for objects defined in this package
image.maigesActNet | Method image for objects defined in this package
image.maigesANOVA | Method image for objects defined in this package
image.maigesRaw | Method image for objects defined in this package
image.maigesRelNetB | Method image for objects defined in this package
image.maigesRelNetM | Method image for objects defined in this package

## -- K --

kmeansM | Function to do k-means cluster analysis
kmeansMde | Function to do k-means cluster analysis

## -- L --

loadData | Load cDNA microarray data tables

## -- M --

maiges | maiges class, store normalised microarray datasets
maiges-class | maiges class, store normalised microarray datasets
maigesActMod | maigesActMod class, store results of functional classification of gene groups
maigesActMod-class | maigesActMod class, store results of functional classification of gene groups
maigesActNet | maigesActNet class, store results of functional classification of gene networks
maigesActNet-class | maigesActNet class, store results of functional classification of gene networks
maigesANOVA | maigesANOVA class, extend maiges class to fit ANOVA models
maigesANOVA-class | maigesANOVA class, extend maiges class to fit ANOVA models
maigesClass | maigesClass class, store results of discrimination (or classification) analysis
maigesClass-class | maigesClass class, store results of discrimination (or classification) analysis
maigesDE | maigesDE class, store results of differential gene expression analysis
maigesDE-class | maigesDE class, store results of differential gene expression analysis
maigesDEcluster | maigesDEcluster class, store results of differential gene expression analysis
maigesDEcluster-class | maigesDEcluster class, store results of differential gene expression analysis
maigesPreRaw | maigesPreRaw class, store pre raw microarray datasets
maigesPreRaw-class | maigesPreRaw class, store pre raw microarray datasets
maigesRaw | maigesRaw class, store raw microarray datasets
maigesRaw-class | maigesRaw class, store raw microarray datasets
maigesRelNetB | maigesRelNetB class, store results of relevance network analysis (Butte's method)
maigesRelNetB-class | maigesRelNetB class, store results of relevance network analysis (Butte's method)
maigesRelNetM | maigesRelNetM class, store results of relevance network analysis (comparing two sample types)
maigesRelNetM-class | maigesRelNetM class, store results of relevance network analysis (comparing two sample types)
MI | Calculate Mutual Information

## -- N --

normLoc | Normalise a cDNA Microarray Object
normOLIN | Normalise a cDNA Microarray Object
normRepLoess | Bootstrap of LOWESS normalisation
normScaleLimma | Scale adjust a cDNA Microarray Object
normScaleMarray | Scale adjust a cDNA Microarray Object

## -- P --

plot | Method plot for objects defined in this package
plot.maiges | Method plot for objects defined in this package
plot.maigesActMod | Method plot for objects defined in this package
plot.maigesActNet | Method plot for objects defined in this package
plot.maigesANOVA | Method plot for objects defined in this package
plot.maigesClass | Method plot for objects defined in this package
plot.maigesDE | Method plot for objects defined in this package
plot.maigesDEcluster | Method plot for objects defined in this package
plot.maigesRaw | Method plot for objects defined in this package
plot.maigesRelNetB | Method plot for objects defined in this package
plot.maigesRelNetM | Method plot for objects defined in this package
plotGenePair | Scatter plots for pair of genes
print | Method to print a nice visualisation of the objects defined in this package
print.maiges | Method to print a nice visualisation of the objects defined in this package
print.maigesActMod | Method to print a nice visualisation of the objects defined in this package
print.maigesActNet | Method to print a nice visualisation of the objects defined in this package
print.maigesANOVA | Method to print a nice visualisation of the objects defined in this package
print.maigesClass | Method to print a nice visualisation of the objects defined in this package
print.maigesDE | Method to print a nice visualisation of the objects defined in this package
print.maigesDEcluster | Method to print a nice visualisation of the objects defined in this package
print.maigesPreRaw | Method to print a nice visualisation of the objects defined in this package
print.maigesRaw | Method to print a nice visualisation of the objects defined in this package
print.maigesRelNetB | Method to print a nice visualisation of the objects defined in this package
print.maigesRelNetM | Method to print a nice visualisation of the objects defined in this package

## -- R --

relNet2TGF | Transform Relevance Network analysis in TGF output
relNet2TGF.maigesRelNetB | Transform Relevance Network analysis in TGF output
relNet2TGF.maigesRelNetM | Transform Relevance Network analysis in TGF output
relNetworkB | Relevance Network analysis
relNetworkM | Relevance Network analysis
robustCorr | Calculate a robust correlation value

## -- S --

selSpots | Select spots to use in normalisation
show | Show a nice visualisation of the objects defined in this package
show-method | Show a nice visualisation of the objects defined in this package
somM | Function to do SOM cluster analysis
somMde | Function to do SOM cluster analysis
summarizeReplicates | Summarise microarray objects
summary | Method summary for the object from this package
summary.maiges | Method summary for the object from this package
summary.maigesActMod | Method summary for the object from this package
summary.maigesActNet | Method summary for the object from this package
summary.maigesANOVA | Method summary for the object from this package
summary.maigesClass | Method summary for the object from this package
summary.maigesDE | Method summary for the object from this package
summary.maigesDEcluster | Method summary for the object from this package
summary.maigesPreRaw | Method summary for the object from this package
summary.maigesRaw | Method summary for the object from this package
summary.maigesRelNetB | Method summary for the object from this package
summary.maigesRelNetM | Method summary for the object from this package

## -- T --

tableClass | Save HTML or CSV tables of good classifiers (cliques)
tablesDE | Save HTML or CSV tables of differentially expressed genes

## -- misc --

[ | Sub-setting methods for maiges objects
[-method | Sub-setting methods for maiges objects