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maigesPack (version 1.36.0)

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

Description

This package uses functions of various other packages together with other functions in a coordinated way to handle and analyse cDNA microarray data

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Version

Version

1.36.0

License

GPL (>= 2)

Maintainer

Gustavo H Esteves

Last Published

February 15th, 2017

Functions in maigesPack (1.36.0)

activeNet

Functional classification of gene networks
contrastsFitM

Compute Contrasts from Linear Model Fit
bootstrapMI

Calculate bootstrap p-values for mutual information (MI) measures
calcA

Method calcA to calculate A values
deGenesANOVA

Function to do differential expression analysis, using ANOVA models
normOLIN

Normalise a cDNA Microarray Object
bootstrapT

Calculate bootstrap p-values for t statistics
[-method

Sub-setting methods for maiges objects
designANOVA

Function to construct design an contrasts matrices for ANOVA models
relNetworkM

Relevance Network analysis
selSpots

Select spots to use in normalisation
normScaleMarray

Scale adjust a cDNA Microarray Object
maigesDE-class

maigesDE class, store results of differential gene expression analysis
coerce-method

Coerce a maiges object to classes defined by packages limma and marray
MI

Calculate Mutual Information
createMaigesRaw

Function to create objects of class maigesRaw
loadData

Load cDNA microarray data tables
maiges-class

maiges class, store normalised microarray datasets
addGeneGrps

Function to load gene groups into maigesPreRaw object
maigesRaw-class

maigesRaw class, store raw microarray datasets
relNetworkB

Relevance Network analysis
normScaleLimma

Scale adjust a cDNA Microarray Object
maigesClass-class

maigesClass class, store results of discrimination (or classification) analysis
image

Method image for objects defined in this package
activeModScoreHTML

Save HTML file with global gene scores from functional gene groups classification
calcW

Method calcW to calculate W values
classifySVM

Function to do discrimination analysis
activeMod

Functional classification of gene groups
addPaths

Function to load gene pathways into maigesPreRaw object
relNet2TGF

Transform Relevance Network analysis in TGF output
kmeansMde

Function to do k-means cluster analysis
tablesDE

Save HTML or CSV tables of differentially expressed genes
deGenes2by2Ttest

Function to do differential expression analysis, comparing only two samples
classifyLDAsc

Function to do discrimination analysis, by the search and choose method
compCorr

Compute correlation differences and their p-values
maigesRelNetB-class

maigesRelNetB class, store results of relevance network analysis (Butte's method)
kmeansM

Function to do k-means cluster analysis
robustCorr

Calculate a robust correlation value
tableClass

Save HTML or CSV tables of good classifiers (cliques)
maigesActMod-class

maigesActMod class, store results of functional classification of gene groups
maigesDEcluster-class

maigesDEcluster class, store results of differential gene expression analysis
bootstrapCor

Calculate bootstrap p-values for correlation measures
plotGenePair

Scatter plots for pair of genes
print

Method to print a nice visualisation of the objects defined in this package
classifySVMsc

Function to do discrimination analysis, by the search and choose method
deGenes2by2Wilcox

Function to do differential expression analysis, comparing only two samples
gastro

Gastro-esophagic dataset
activeNetScoreHTML

Save HTML file with scores and p-values from functional gene networks classification
heatmapsM

Function to plot heatmaps separating groups generated by SOM or k-means
boxplot

Method boxplot for objects defined in this package
classifyKNNsc

Function to do discrimination analysis, by the search and choose method
hierM

Function to do hierarchical cluster analysis
createTDMS

Create a tab delimited file for TIGR MeV
deGenes2by2BootT

Function to do differential expression analysis, comparing only two samples
classifyLDA

Function to do discrimination analysis
maigesRelNetM-class

maigesRelNetM class, store results of relevance network analysis (comparing two sample types)
maigesPreRaw-class

maigesPreRaw class, store pre raw microarray datasets
classifyKNN

Function to do discrimination analysis
dim

Retrieve the dimension of microarray objects
hierMde

Function to do hierarchical cluster analysis
summary

Method summary for the object from this package
getLabels

Method getLabels to pick gene and sample labels
normRepLoess

Bootstrap of LOWESS normalisation
maigesANOVA-class

maigesANOVA class, extend maiges class to fit ANOVA models
show-method

Show a nice visualisation of the objects defined in this package
somM

Function to do SOM cluster analysis
plot

Method plot for objects defined in this package
maigesActNet-class

maigesActNet class, store results of functional classification of gene networks
somMde

Function to do SOM cluster analysis
summarizeReplicates

Summarise microarray objects
normLoc

Normalise a cDNA Microarray Object