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Expression Analysis

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

Evaluate gene expression data and identify differentially expressed genes using hypothesis tests. Use various machine learning functions to train classifier models, perform principal component analysis, rank features, and impute missing data. Visualize microarray data using intensity versus ratio (IR) plots, box plots, or log-log plots.


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mattestPerform two-sample t-test to evaluate differential expression of genes from two experimental conditions or phenotypes
mafdrEstimate positive false discovery rate for multiple hypothesis testing
nbintestUnpaired hypothesis test for count data with small sample sizes
metafeaturesAttractor metagene algorithm for feature engineering using mutual information-based learning
rankfeaturesRank key features by class separability criteria
randfeaturesGenerate randomized subset of features
knnimputeImpute missing data using nearest-neighbor method
crossvalindGenerate indices for training and test sets
classperfEvaluate classifier performance
mavolcanoplotCreate significance versus gene expression ratio (fold change) scatter plot of microarray data
mairplotCreate intensity versus ratio scatter plot of microarray data
maboxplotCreate box plot for microarray data
maloglogCreate loglog plot of microarray data
mapcaplotCreate Principal Component Analysis (PCA) plot of microarray data
redbluecmapCreate red and blue colormap
redgreencmapCreate red and green colormap
probesetplotPlot Affymetrix probe set intensity values


DataMatrixCreate DataMatrix object
DataMatrix objectData structure encapsulating data and metadata from microarray experiment so that it can be indexed by gene or probe identifiers and by sample identifiers
bioma.ExpressionSetContain data from microarray gene expression experiment data values from microarray experiment metadata from microarray experiment experiment information from microarray gene expression experiment
NegativeBinomialTestUnpaired hypothesis test result
HeatMapObject containing matrix and heatmap display properties
clustergramObject containing hierarchical clustering analysis data