Function reference • CytoPipeline

All functions
`show(<CytoPipeline>)` `CytoPipeline(<missing>)` `CytoPipeline(<list>)` `CytoPipeline(<character>)` `as.list(<CytoPipeline>)` `experimentName()` `experimentName<-`() `sampleFiles()` `sampleFiles<-`() `pData()` `pData<-`()	CytoPipeline package
`CytoPipeline-class` `CytoPipeline-class,` `CytoPipelineClass`	CytoPipeline class
`CytoProcessingStep()` `show(<CytoProcessingStep>)` `executeProcessingStep()` `getCPSName()` `getCPSFUN()` `getCPSARGS()` `as.list(<CytoProcessingStep>)` `as.json.CytoProcessingStep()` `from.json.CytoProcessingStep()`	Cyto Processing step
`OMIP021Samples`	OMIP021Samples dataset
`aggregateAndSample()`	Aggregate and sample multiple flow frames of a flow set together
`appendCellID()`	append 'Original_ID' column to a flowframe
`applyScaleTransforms()`	apply scale transforms
`areFluoCols()`	find flow frame columns that represent fluorochrome channel
`areSignalCols()`	find flow frame columns that represent true signal
`compensateFromMatrix()`	compensation of fcs file(s) from matrix
`computeScatterChannelsLinearScale()`	compute linear transformation of scatter channels found in ff, based on 5% and 95% of referenceChannel, set as target. If there is a transformation defined in transList for referenceChannel, it is applied first, before computing quantiles. Then the computed linear transformations (or each scatter channel) are added into the transfo_list. -A channels are computed, and same linear transformation is then applied to corresponding -W and -H channels (if they exist in ff).
`estimateScaleTransforms()`	estimates scale tranformations
`execute()`	executing CytoPipeline object
`export2JSONFile()`	exporting CytoPipeline objects
`findTimeChannel()`	find time channel in flowSet/flowFrame
`getAcquiredCompensationMatrix()`	extract compensation matrix from a flowCore::flowFrame
`getChannelNamesFromMarkers()`	get channel names from markers
`getFCSFileName()`	get fcs file name
`getTransfoParams()`	get tranformation parameters for a specific channel
`ggplotEvents()`	plot events in 1D or 2D, using ggplot2
`ggplotFilterEvents()`	plot filtered events in 2D, using ggplot
`ggplotFlowRate()`	plot flow rate as a function of time, using ggplot2
`addProcessingStep()` `removeProcessingStep()` `getNbProcessingSteps()` `getProcessingStep()` `getProcessingStepNames()` `cleanProcessingSteps()` `showProcessingSteps()`	handling processing steps in CytoPipeline objects
`getCytoPipelineExperimentNames()` `getCytoPipelineObjectFromCache()` `getCytoPipelineObjectInfos()` `getCytoPipelineFlowFrame()` `getCytoPipelineScaleTransform()` `plotCytoPipelineProcessingQueue()`	inspect CytoPipeline results objects
`deleteCytoPipelineCache()` `buildCytoPipelineFromCache()` `checkCytoPipelineConsistencyWithCache()`	interaction between CytoPipeline object and disk cache
`qualityControlFlowAI()`	perform QC with flowAI
`qualityControlPeacoQC()`	perform QC with PeacoQC
`readRDSObject()`	read RDS object
`readSampleFiles()`	Read fcs sample files
`removeChannels()`	remove channels from a flowFrame
`removeDeadCellsManualGate()`	remove dead cells from a flowFrame using manual gating
`removeDebrisManualGate()`	remove debris from a flowFrame using manual gating
`removeDoubletsCytoPipeline()`	remove doublets from a flowFrame, using CytoPipeline custom algorithm
`removeMarginsPeacoQC()`	remove margin events using PeacoQC
`runCompensation()`	compensate with additional options
`singletsGate()`	Clean doublet events from flow cytometry data
`subsample()`	sub-sampling of a flowFrame
`updateMarkerName()`	update marker name of a given flowFrame channel
`writeFlowFrame()`	write flowFrame to disk

Reference

All functions