ECL`

AnalyzeCompensationMatrix

AnalyzeCompensationMatrix[FlowCytometryProtocol]⟹CompensationMatrix

uses the AdjustmentSampleData collected in the provided FlowCytometryProtocol to compute the CompensationMatrix that corrects for fluorophore signal overlap.

Details

AnalyzeCompensationMatrix computes spillover and compensation matrices using event peak areas.

Input

Output

General Options

Method Options

Examples

open allclose all

Basic Examples (5)

Compute a compensation matrix for each flow cytometry protocol in a list:

Compute a compensation matrix from a flow cytometry protocol with CompensationSamplesIncluded of True. The compensation matrix is used to correct for fluorophore spillover between detectors:

If the input protocol contains an UnstainedSample, it will be used as a universal negative. Thresholds will not be used because populations will be clearly defined. The preview will show the separation between the positive and negative populations for each compensation sample:

If the input protocol contains CompensationSamples which contain both positive and negative controls, the command builder preview will generate an interactive app which can be used to set the thresholds between positive and negative populations. Please load the function call in the builder to use this app:

Retrieve the numerical compensation matrix from a CompensationMatrix analysis object:

Options (5)

DetectionLabels (1)

Override the DetectionLabels in the input protocol. For illustrative purposes, the function call below overrides labels with the identity models for some standard amino acids:

DetectionThresholds (2)

If input protocol does not use an unstained global negative, for each detector (and corresponding AdjustmentSampleData), specify the signal threshold above which a cell will be considered to be positive for the label assigned to that detector:

If the input protocol uses an unstained sample as a global negative (i.e. UnstainedSampleData is informed), then DetectionThresholds will be ignored:

Detectors (1)

Specify a subset of the detectors to use for CompensationMatrix analysis. Detectors present in the protocol but not specified here will be presumed not to spillover into other channels:

Template (1)

Use option settings from an existing analysis object in this compensation matrix analysis. Here, the Detectors and DetectionThreshold options are inherited from the template analysis object:

Messages (8)

AdjustmentDataNotFound (1)

Warning shows if input protocol has AdjustmentSamplesIncluded equal to True, but one or more AdjustmentSamples (index-matched to Detectors) do not have a corresponding data object in AdjustmentSampleData. Analysis will proceed, and the detectors missing AdjustmentSampleData will be assumed not to spillover into other detectors:

DetectorsNotInProtocol (1)

All detectors in the Detectors option must be a member of the Detectors field of input protocol:

DetectorsNotSet (2)

The DetectionLabels option cannot be set unless the Detectors option has been explicitly set:

The DetectionThresholds option cannot be set unless the Detectors option has been explicitly set:

DuplicateDetectors (1)

The Detectors option cannot contain duplicates:

EmptyPartition (1)

CompensationMatrix cannot be calculated if thresholds do not result in separation of adjustment data into a positive and negative population:

NoCompensationSamplesFound (1)

Error shows if no compensation could be found in input protocol. The input protocol must have CompensationSamplesIncluded equal to True, and have one or more data objects linked in its AdjustmentSampleData field:

UnusedThresholds (1)

DetectionThresholds cannot be used if the input protocol has UnstainedSampleData. This unstained sample data is treated as a global negative, so the thresholding option will be ignored:

Last modified on Tue 9 Sep 2025 10:46:55