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- Page 9 and 10: WGCNA-package 9collection of eigeng
- Page 11 and 12: addErrorBars 11Valueno.true negativ
- Page 13 and 14: addGuideLines 13addGuideLinesAdd ve
- Page 15 and 16: adjacency 15DetailsValueNoteselectC
- Page 17 and 18: adjacency.splineReg 17ValueAn adjac
- Page 19 and 20: AFcorMI 19Examples#Simulate a data
- Page 21 and 22: allowWGCNAThreads 21allowWGCNAThrea
- Page 23 and 24: automaticNetworkScreeningGS 23autom
- Page 25 and 26: icor 25pearsonFallbackSpecifies whe
- Page 27 and 28: icorAndPvalue 27DetailsThe function
- Page 29 and 30: lockwiseConsensusModules 29# Consen
- Page 31 and 32: lockwiseConsensusModules 31pearsonF
- Page 33 and 34: lockwiseConsensusModules 33minKMEto
- Page 35 and 36: lockwiseConsensusModules 35NoteTOMF
- Page 37 and 38: lockwiseIndividualTOMs 37nThreads =
- Page 39 and 40: lockwiseIndividualTOMs 39Valuewithi
- Page 41 and 42: lockwiseModules 41pearsonFallback =
- Page 43 and 44: lockwiseModules 43maxPOutliers only
- Page 45 and 46: BloodLists 45MEsOKlogical indicatin
- Page 47 and 48: checkSets 47ArgumentsadjMatsimilari
- Page 49 and 50: chooseTopHubInEachModule 49ValueBot
- Page 51 and 52: coClustering 51coClusteringCo-clust
- Page 53 and 54: coClustering.permutationTest 53verb
- Page 55 and 56: collapseRows 55rowIDcharacter vecto
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collapseRows 57selectedRowis a logi
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collapseRowsUsingKME 59ArgumentsMMG
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conformityBasedNetworkConcepts 61co
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conformityDecomposition 63Descripti
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consensusDissTOMandTree 65A=matrix(
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consensusKME 67UsageconsensusKME(mu
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consensusKME 69meta.Z.RootDoFWeight
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consensusMEDissimilarity 71Z.kME1.S
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consensusProjectiveKMeans 73Details
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cor 75unmergedClustersa numerical v
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cor 77NoteThe implementation uses t
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corPredictionSuccess 79ReferencesPe
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corPvalueStudent 81corPvalueStudent
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coxRegressionResiduals 83DetailsVal
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cutreeStaticColor 85cutreeStaticCol
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exportNetworkToCytoscape 87Author(s
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fixDataStructure 89ValueA data fram
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GOenrichmentAnalysis 91MARDensitya
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GOenrichmentAnalysis 93backgroundTy
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goodGenes 95UsagegoodGenes(datExpr,
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goodSamples 97ValueA logical vector
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goodSamplesGenesMS 99DetailsThis fu
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greenBlackRed 101ArgumentsmultiExpr
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GTOMdist 103ValueA vector of colors
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Inline display of progress 105Argum
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keepCommonProbes 107Author(s)Steve
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labeledBarplot 109fileNameName of t
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labeledHeatmap 111UsagelabeledHeatm
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labeledHeatmap 113Examples# This ex
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labels2colors 115ValueNone.Author(s
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matchLabels 117ValueA symmetric mat
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mergeCloseModules 119maxpowerdiagEn
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mergeCloseModules 121DetailsValueus
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metaAnalysis 123corFnccorOptionsCor
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metaAnalysis 125qValueExtremeScale.
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metaZfunction 127metaZfunctionMeta-
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moduleEigengenes 129Argumentsexprco
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moduleMergeUsingKME 131allPCisPCisH
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moduleNumber 133set.seed(100)MEturq
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modulePreservation 135savePermutedS
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modulePreservation 137DetailsValueT
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multiData.eigengeneSignificance 139
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multiSetMEs 141universalColorsAlter
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mutualInfoAdjacency 143allOKallPCis
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mutualInfoAdjacency 145tual informa
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nearestCentroidPredictor 147Usagene
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nearestCentroidPredictor 149verbose
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nearestNeighborConnectivity 151Argu
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networkConcepts 153ValueA matrix in
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networkConcepts 155Eigengenethe fir
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networkScreeningGS 157blockSizebloc
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nPresent 159Author(s)Peter Langfeld
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orderBranchesUsingHubGenes 161Value
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orderMEs 163colorh2 [selectBranch(t
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overlapTableUsingKME 165ValueA list
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pickHardThreshold 167results = over
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pickSoftThreshold 169pickSoftThresh
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plotClusterTreeSamples 171plotClust
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plotColorUnderTree 173plotColorUnde
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plotDendroAndColors 175titlecharact
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plotEigengeneNetworks 177DetailsVal
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plotEigengeneNetworks 179cex.preser
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plotMEpairs 181plotMEpairsPairwise
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plotNetworkHeatmap 183See Alsobarpl
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populationMeansInAdmixture 185Detai
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pquantile 187Argumentsprob A number
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preservationNetworkConnectivity 189
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projectiveKMeans 191Usageprojective
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proportionsInAdmixture 193calculate
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qvalue 195DetailsValueFor compatibi
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qvalue.restricted 197qvalue.restric
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ankPvalue 199DetailsValueThe functi
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ecutBlockwiseTrees 201UsagerecutBlo
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ecutBlockwiseTrees 203DetailsValueF
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ecutConsensusTrees 205TOMFilesdendr
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edWhiteGreen 207NoteunmergedColorsm
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emoveGreyME 209removeGreyMERemoves
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scaleFreeFitIndex 211scaleFreeFitIn
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setCorrelationPreservation 213Forma
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signedKME 215ReferencesBin Zhang an
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simulateDatExpr 217UsagesimulateDat
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simulateDatExpr5Modules 219datExprs
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simulateEigengeneNetwork 221simulat
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simulateMultiExpr 223ValueIf signed
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simulateMultiExpr 225submoduleSpaci
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sizeGrWindow 227DetailsModule eigen
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spaste 229verboseindentinteger leve
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standardScreeningBinaryTrait 231Usa
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standardScreeningCensoredTime 233#
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standardScreeningNumericTrait 235pV
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stat.diag.da 237Author(s)Sandrine D
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stratifiedBarplot 239ArgumentsexpAl
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swapTwoBranches 241corOptionsnetwor
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TOMplot 243sizeGrWindow(12,9);# par
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TOMsimilarityFromExpr 245DetailsThe
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TrueTrait 247indentindentation for
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TrueTrait 249divides by the slope o
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userListEnrichment 251powercorFncco
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userListEnrichment 253matter what i
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userListEnrichment 255MouseMeta ==>
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vectorTOM 257UsagevectorTOM(datExpr
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verboseBarplot 259DetailsThis funct
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verboseIplot 261verboseIplotScatter
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verboseScatterplot 263Argumentsxysa
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votingLinearPredictor 265priorWeigh
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Index∗Topic \textasciitildekwd1ov
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INDEX 269verboseBarplot, 258verbose
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INDEX 271pmin, 187poly, 17populatio