\name{computeDatasetSignature} \alias{computeDatasetSignature} \alias{computeDatasetSignature,GenomicAnnotationsForPREDA-method} \title{ Function to compute dataset signature for recurrent significant genomic regions } \description{ Function to compute dataset signature for recurrent significant genomic regions } \usage{ # computeDatasetSignature(.Object, genomicRegionsList=genomicRegionsList, # multTestCorrection="fdr", signature_qval_threshold=0.05, # returnRegions=TRUE, use.referencePositions=TRUE) computeDatasetSignature(.Object, ...) } \arguments{ \item{.Object}{ Object of class GenomicAnnotationsForPREDA } \item{\dots}{ See below \describe{ \item{genomicRegionsList:}{ List of genomicRegions objects for which the recurrent overlapping regions will be evaluated } \item{multTestCorrection:}{ Multiple testing correction that will be adopted to correct the statistic p-values. Possible values are "fdr", for benjamini and Hochberg multiple testing correction and "qvalue" for p-values correction performed with qvalue package. } \item{signature_qval_threshold:}{ Threshold used to select significant regions resulting from the dataset signature statistic } \item{returnRegions:}{ Logical, if TRUE (default) the genomic regions constituting the daaset signature are returned, otherwise a PREDAresults object containing dataset signature statistics is returned. } \item{use.referencePositions:}{ Logical, if TRUE the input reference positions used for PREDA analysis wil be used to identify significant genomic regions boundaries as well. } } } } \details{ The function adopts a binomial test to identify significant recurrence of genomic regions across multiple dataset sampels. } \value{ A GenomicRegions object (if returnRegions = TRUE) or a PREDAresults object containing dataset signature statistics (if returnRegions = FALSE) } \author{ Francesco Ferrari } \seealso{ \code{\linkS4class{GenomicRegions}}, \code{\linkS4class{PREDAResults}} } \examples{ \dontrun{ require(PREDAsampledata) data(SODEGIRCNanalysisResults) data(GEDataForPREDA) SODEGIR_CN_GAIN<-PREDAResults2GenomicRegions( SODEGIRCNanalysisResults, qval.threshold=0.01, smoothStatistic.tail="upper", smoothStatistic.threshold=0.1) CNgain_signature<-computeDatasetSignature(GEDataForPREDA, genomicRegionsList=SODEGIR_CN_GAIN) } }