Function reference • decorate

All functions

boxM(): Box's M-test

boxM_fast(): Box's M-test

boxM_permute(): Box's M-test

collapseClusters(): Collapse clusters based on jaccard index

combineResults(): Combine results into a single data.frame

corSubsetPairs(): Compute correlations between pairs of features

corrMatrix.test(): Test difference between two correlation matricies

countClusters(): Count clusters on each chromosome

createClusters(): Create cluster from list of hclust objects

createCorrelationMatrix(): Create correlation matrix

decorateData decorateData decorateData: Simulated data to show correlation clustering

delaneau.score(): Score impact of each sample on correlation sturucture

delaneau.test(): Test association between correlation sturucture and variable

.evalDiffCorr(): Internal .evalDiffCorr

epiclust-class: Class epiclust

epiclustDiscreteList-class: Class epiclustDiscreteList

epiclustDiscreteListContain-class: Class epiclustDiscreteListContain

epiclustList-class: Class epiclustList

evalDiffCorr(): Evaluate Differential Correlation

evaluateCorrDecay(): Evaluate the decay of correlation versus distance between features

extractCorrelationScores(): Extract sample-level correlation scores

filterClusters(): Extract subset of clusters

getClusterNames(): Get name of each cluster

getClusterRanges(): Get genome coordinates for each cluster

getFeaturesInCluster(): Get feature names in selected cluster

getFeaturesInClusterList(): Get feature names in selected cluster

getPeakDistances(): Compute distance between peaks

getSubset(): Extract subset of data points

get_exon_coords(): Get coordinates of exons

ggplot_by_sampling(): Plot by subsampling in each bin

jaccard(): Evaluate Jaccard index

makeImageRect(): Convert correlation matrix into triangle plot

plotClusterSegments(): Plot cluster segments

plotCompareCorr(): Plot two correlation matrices together

plotCorrDecay(): Plot correlation delay

plotCorrTriangle(): Plot triangle of correlation matrix

plotDecorate(): Plot decorate analysis

plotDensityPoints(): Plot density as color, add outlier points

plotEnsGenes(): Plot ENSEMBL genes

plotGenes(): Plot genes from a specified region of the human genome.

plotPairwiseScatter(): Scatter plot of all pairs of variables stratified by test variable

plotScatterPairs(): Scatter plot of all pairs of variables stratified by test variable

retainClusters(): Retain clusters by applying filter

runFastStat(): Test difference in correlation using closed form tests

runOrderedClustering(): Run hierarchical clustering preserving order

runOrderedClusteringGenome(): Run hierarchical clustering preserving order

runPermutedData(): Run hierarchical clustering permuting features

sLEDresults-class: An S4 class that stores results of sLED analysis

scoreClusters(): Compute scores for each cluster

sle.score(): Score impact of each sample on sparse leading eigen-value

sle.test(): Test association between sparse leading eigen-value and variable

`[`(<epiclustDiscreteListContain>,<ANY>,<ANY>,<ANY>): Allow subsetting of epiclustDiscreteListContain

summary(<sLEDresults>): Summarize sLED analysis

whichCluster(): Find which cluster a peak is in