Performs clustering of CAGE derived expression across multiple experiments, both at level of individual TSSs or entire clusters of TSSs.
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getExpressionProfiles(object, what, tpmThreshold = 5, nrPassThreshold = 1, method = "som", xDim = 5, yDim = 5)
At which level should the expression clustering be done. Can be either
Only CTSSs or consensus clusters (depending on
Method to be used for expression clustering. Can be either
Expression clustering can be done at level of individual CTSSs, in which case the feature vector used as input for clustering algorithm contains log-transformed and scaled (divided by standard deviation) normalized CAGE signal at individual TSS across multiple experiments. Only TSSs with normalized CAGE signal
>= tpmThreshold in at least
nrPassThreshold CAGE experiments are used for expression clustering. However, CTSSs along the genome can be spatially clustered into tag clusters for each experiment separately using the
clusterCTSS function, and then aggregated across experiments into consensus clusters using
aggregateTagClusters function. Once the consensus clusters have been created, expression clustering at the level of these wider genomic regions (representing entire promoters rather than individual TSSs) can be performed. In that case the feature vector used as input for clustering algorithm contains normalized CAGE signal within entire consensus cluster across multiple experiments, and threshold values in
nrPassThreshold are applied to entire consensus clusters.
what = "CTSS" the slots
CTSSexpressionClasses will be occupied, and if
what = "consensusClusters" the slots
consensusClustersExpressionClasses of the provided
CAGEset object will be occupied with the results of expression clustering. Labels of expression classes (clusters) can be retrieved using
expressionClasses function, and elements belonging to a specific expression class can be selected using
Toronen et al. (1999) Analysis of gene expression data using self-organizing maps, FEBS Letters 451:142-146.
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