Propagating Uncertainty in Microarray Analysis(including Affymetrix tranditional 3' arrays and exon arrays and Human Transcriptome Array 2.0)


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Documentation for package ‘puma’ version 3.42.0

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B C D E F G H I J L M N O P R S T W

puma-package puma - Propagating Uncertainty in Microarray Analysis

-- B --

bcomb Combining replicates for each condition

-- C --

calcAUC Calculate Area Under Curve (AUC) for a standard ROC plot.
calculateFC Calculate differential expression between conditions using FC
calculateLimma Calculate differential expression between conditions using limma
calculateTtest Calculate differential expression between conditions using T-test
class:DEResult Class DEResult
class:exprReslt Class exprReslt
class:pumaPCARes Class pumaPCARes
Clust.exampleE The example data of the mean gene expression levels
Clust.exampleStd The example data of the standard deviation for gene expression levels
clusterApplyLBDots clusterApplyLB with dots to indicate progress
clusterNormE Zero-centered normalisation
clusterNormVar Adjusting expression variance for zero-centered normalisation
Clustii.exampleE The example data of the mean gene expression levels
Clustii.exampleStd The example data of the standard deviation for gene expression levels
compareLimmapumaDE Compare pumaDE with a default Limma model
createContrastMatrix Automatically create a contrast matrix from an ExpressionSet and optional design matrix
createDesignMatrix Automatically create a design matrix from an ExpressionSet
create_eset_r Create an ExpressionSet from a PPLR matrix

-- D --

DEMethod Class DEResult
DEMethod-method Class DEResult
DEMethod<- Class DEResult
DEMethod<--method Class DEResult
DEResult Class DEResult
DEResult-class Class DEResult

-- E --

erfc The complementary error function
eset_mmgmos An example ExpressionSet created from the Dilution data with mmgmos
exampleE The example data of the mean gene expression levels
exampleStd The example data of the standard deviation for gene expression levels
exprReslt Class exprReslt
exprReslt-class Class exprReslt

-- F --

FC Class DEResult
FC-method Class DEResult
FC<- Class DEResult
FC<--method Class DEResult

-- G --

gmhta Compute gene and transcript expression values and standard deviatons from hta2.0 CEL Files
gmoExon Compute gene and transcript expression values and standard deviatons from exon CEL Files

-- H --

hcomb Combining replicates for each condition with the true gene expression
hgu95aphis Estimated parameters of the distribution of phi

-- I --

igmoExon Separately Compute gene and transcript expression values and standard deviatons from exon CEL Files by the conditions.

-- J --

just.mgmos Compute mgmos Directly from CEL Files
just.mmgmos Compute mmgmos Directly from CEL Files
justmgMOS Compute mgmos Directly from CEL Files
justmmgMOS Compute mmgmos Directly from CEL Files

-- L --

legend2 A legend which allows longer lines
license.puma Print puma license

-- M --

matrixDistance Calculate distance between two matrices
mgmos modified gamma Model for Oligonucleotide Signal
mmgmos Multi-chip modified gamma Model for Oligonucleotide Signal

-- N --

newtonStep PUMA Principal Components Analysis
normalisation.gs Global scaling normalisation
numberOfContrasts Class DEResult
numberOfContrasts-method Class DEResult
numberOfGenes Class DEResult
numberOfGenes-method Class DEResult
numberOfProbesets Class DEResult
numberOfProbesets-method Class DEResult
numFP Number of False Positives for a given proportion of True Positives.
numOfFactorsToUse Determine number of factors to use from an ExpressionSet
numTP Number of True Positives for a given proportion of False Positives.

-- O --

orig_pplr Probability of positive log-ratio

-- P --

pLikeValues Class DEResult
pLikeValues-method Class DEResult
plot-method Plot method for pumaPCARes objects
plot-methods Plot method for pumaPCARes objects
plot.pumaPCARes Plot method for pumaPCARes objects
plotErrorBars Plot mean expression levels and error bars for one or more probesets
plotHistTwoClasses Stacked histogram plot of two different classes
plotROC Receiver Operator Characteristic (ROC) plot
plotWhiskers Standard errors whiskers plot
PMmmgmos Multi-chip modified gamma Model for Oligonucleotide Signal using only PM probe intensities
pplr Probability of positive log-ratio
pplrUnsorted Return an unsorted matrix of PPLR values
prcfifty Class exprReslt
prcfifty-method Class exprReslt
prcfifty<- Class exprReslt
prcfifty<--method Class exprReslt
prcfive Class exprReslt
prcfive-method Class exprReslt
prcfive<- Class exprReslt
prcfive<--method Class exprReslt
prcninfive Class exprReslt
prcninfive-method Class exprReslt
prcninfive<- Class exprReslt
prcninfive<--method Class exprReslt
prcsevfive Class exprReslt
prcsevfive-method Class exprReslt
prcsevfive<- Class exprReslt
prcsevfive<--method Class exprReslt
prctwfive Class exprReslt
prctwfive-method Class exprReslt
prctwfive<- Class exprReslt
prctwfive<--method Class exprReslt
puma puma - Propagating Uncertainty in Microarray Analysis
pumaClust Propagate probe-level uncertainty in model-based clustering on gene expression data
pumaClustii Propagate probe-level uncertainty in robust t mixture clustering on replicated gene expression data
pumaComb Combining replicates for each condition
pumaCombImproved Combining replicates for each condition with the true gene expression
pumaDE Calculate differential expression between conditions
pumaDEUnsorted Return an unsorted matrix of PPLR values
pumaFull Perform a full PUMA analysis
pumaNormalize Normalize an ExpressionSet
pumaPCA PUMA Principal Components Analysis
pumaPCAEstep PUMA Principal Components Analysis
pumaPCAExpectations Class pumaPCAExpectations
pumaPCAExpectations-class Class pumaPCAExpectations
pumaPCALikelihoodBound PUMA Principal Components Analysis
pumaPCALikelihoodCheck PUMA Principal Components Analysis
pumaPCAModel Class pumaPCAModel
pumaPCAModel-class Class pumaPCAModel
pumaPCANewtonUpdateLogSigma PUMA Principal Components Analysis
pumaPCARemoveRedundancy PUMA Principal Components Analysis
pumaPCARes Class pumaPCARes
pumaPCARes-class Class pumaPCARes
pumaPCASigmaGradient PUMA Principal Components Analysis
pumaPCASigmaObjective PUMA Principal Components Analysis
pumaPCAUpdateCinv PUMA Principal Components Analysis
pumaPCAUpdateM PUMA Principal Components Analysis
pumaPCAUpdateMu PUMA Principal Components Analysis
pumaPCAUpdateW PUMA Principal Components Analysis

-- R --

removeUninformativeFactors Remove uninformative factors from the phenotype data of an ExpressionSet

-- S --

se.exprs Class exprReslt
se.exprs-method Class exprReslt
se.exprs<- Class exprReslt
se.exprs<--method Class exprReslt
show-method Class DEResult
show-method Class exprReslt
statistic Class DEResult
statistic-method Class DEResult
statistic<- Class DEResult
statistic<--method Class DEResult
statisticDescription Class DEResult
statisticDescription-method Class DEResult
statisticDescription<- Class DEResult
statisticDescription<--method Class DEResult

-- T --

topGeneIDs Class DEResult
topGeneIDs-method Class DEResult
topGenes Class DEResult
topGenes-method Class DEResult

-- W --

write.reslts Class exprReslt
write.reslts-method Class DEResult
write.reslts-method Class exprReslt
write.reslts-method Class pumaPCARes