Unified Approach for Simultaneous Gene Clustering and Differential Expression Identification


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Documentation for package ‘EBarrays’ version 2.58.0

Help Pages

checkCCV Various plotting routines in the EBarrays package
checkModel Various plotting routines in the EBarrays package
checkVarsMar Various plotting routines in the EBarrays package
checkVarsQQ Various plotting routines in the EBarrays package
coerce-method Class of Families to be used in the EBarrays package
crit.fun Find posterior probability threshold to control FDR
eb.createFamilyGG Class of Families to be used in the EBarrays package
eb.createFamilyLNN Class of Families to be used in the EBarrays package
eb.createFamilyLNNMV Class of Families to be used in the EBarrays package
ebarraysEMfit-class Implements EM algorithm for gene expression mixture model
ebarraysFamily-class Class of Families to be used in the EBarrays package
ebarraysPatterns-class Utility functions for the EBarrays package
ebarraysPostProb-class Calculates posterior probabilities for expression patterns
ebPatterns Utility functions for the EBarrays package
ebplots Various plotting routines in the EBarrays package
emfit Implements EM algorithm for gene expression mixture model
emfit-method Implements EM algorithm for gene expression mixture model
gould A dataset of class matrix
plot.ebarraysEMfit Various plotting routines in the EBarrays package
plotCluster Various plotting routines in the EBarrays package
plotMarginal Various plotting routines in the EBarrays package
postprob Calculates posterior probabilities for expression patterns
postprob-method Calculates posterior probabilities for expression patterns
show-method Class of Families to be used in the EBarrays package
show-method Implements EM algorithm for gene expression mixture model
show-method Calculates posterior probabilities for expression patterns
show-method Utility functions for the EBarrays package
utilities Utility functions for the EBarrays package