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Expression Analysis

Identify, visualize, and classify differentially expressed genes and expression profiles


mattest Perform two-sample t-test to evaluate differential expression of genes from two experimental conditions or phenotypes
mafdr Estimate false discovery rate (FDR) for multiple hypothesis testing
mavolcanoplot Create significance versus gene expression ratio (fold change) scatter plot of microarray data
mairplot Create intensity versus ratio scatter plot of microarray data
maboxplot Create box plot for microarray data
maloglog Create loglog plot of microarray data
mapcaplot Create Principal Component Analysis (PCA) plot of microarray data
nbintest Unpaired hypothesis test for short-read count data with small sample sizes
clustergram Compute hierarchical clustering, display dendrogram and heat map, and create clustergram object
redbluecmap Create red and blue colormap
redgreencmap Create red and green colormap
probesetplot Plot Affymetrix probe set intensity values
metafeatures Attractor metagene algorithm for feature engineering using mutual information-based learning
rankfeatures Rank key features by class separability criteria
randfeatures Generate randomized subset of features
knnimpute Impute missing data using nearest-neighbor method
classperf Evaluate performance of classifier
crossvalind Generate cross-validation indices


DataMatrix Create DataMatrix object
DataMatrix object Data structure encapsulating data and metadata from microarray experiment so that it can be indexed by gene or probe identifiers and by sample identifiers
bioma.ExpressionSet Contain data from microarray gene expression experiment Contain data values from microarray experiment Contain metadata from microarray experiment Contain experiment information from microarray gene expression experiment
NegativeBinomialTest Unpaired hypothesis test result
HeatMap Display heat map of matrix data and create HeatMap object
HeatMap object Object containing matrix and heat map display properties
clustergram object Object containing hierarchical clustering analysis data


Analyzing Gene Expression Profiles

Analyze microarray data for patterns and plot the results.

Managing Gene Expression Data in Objects

Overview of objects for Microarray Gene Expression Data

Representing Expression Data Values in DataMatrix Objects

Construct DataMatrix objects, get and set properties, and access data.

Representing Expression Data Values in ExptData Objects

Construct ExptData objects, use properties and methods, and access data.

Representing Sample and Feature Metadata in MetaData Objects

Construct MetaData objects, use properties and methods, and access data.

Representing Experiment Information in a MIAME Object

Construct MIAME objects, use properties and methods, and access data.

Representing All Data in an ExpressionSet Object

Construct ExpressionSet objects, use properties and methods, and access data.

Exploring Microarray Gene Expression Data

This example shows how to identify differentially expressed genes from microarray data and uses Gene Ontology to determine significant biological functions that are associated to the down- and up-regulated genes.

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