Auto Gating QC Flow Cytometer Population Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing QC experiments often fail due to QC impurities or noise, requiring stringent conditions for high purity and cleanliness, leading to frequent re-adjustment of equipment parameters and decreased user experience.
Innovation Solution
A method for auto gating of QC based on population analysis, involving the use of QC beads to collect and analyze data, adjust acquisition parameters, and perform multi-peak data analysis to accurately determine gate positions, even in conditions with high impurity or noise levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If one-dimensional histogram analysis is used to determine QC bead gate position, then the method is simple to operate, but it requires high purity QC beads sample and clean device conditions
Solution Approach 1:
The patent transitions from one-dimensional histogram analysis to two-dimensional population analysis by plotting FSC versus SSC parameters. This dimensional expansion allows the system to distinguish QC beads from impurities and noise based on their characteristic scattering patterns, enabling accurate gate position determination even in samples with contamination or varying purity levels.
Solution Approach 2:
The patent changes the analysis parameters from single-parameter intensity distribution to multi-parameter scattering characteristics (FSC and SSC). By analyzing the combined information from forward scatter and side scatter parameters, the system can identify QC bead populations more robustly against impurities and noise, improving reliability without complicating the operational workflow.
2Measurement precision
If stringent purity and cleanliness conditions are imposed on QC beads sample, then accurate gate positioning can be achieved, but the pass rate of QC experiments decreases due to frequent failures
Solution Approach 1:
The patent extracts the characteristic FSC-SSC scattering signature of QC beads from the mixed population. By focusing on the specific two-dimensional distribution pattern of QC beads rather than requiring overall sample purity, the system can accurately identify gate positions even when impurities are present, thereby improving both accuracy and reliability simultaneously.
Solution Approach 2:
The patent introduces a two-dimensional FSC-SSC parameter space as an intermediary analysis layer between raw data and gate position determination. This intermediary representation filters out the effect of impurities and noise, allowing accurate gate positioning to be achieved under more relaxed sample conditions, thus improving QC experiment pass rate.
3Measurement precision
If manual re-adjustment of equipment parameters and repeated cleaning is performed to meet QC conditions, then measurement accuracy can be maintained, but time consumption and user experience deteriorate
Solution Approach 1:
The patent enables the system to automatically adapt to varying sample conditions through population-based analysis. The method self-adjusts by identifying QC bead populations based on their FSC-SSC characteristics without requiring manual parameter adjustment or repeated cleaning cycles, thereby maintaining measurement accuracy while significantly reducing time loss and improving user experience.
Solution Approach 2:
The patent implements a dynamic analysis approach that adapts to the actual sample conditions rather than requiring fixed predetermined conditions. The population analysis method dynamically identifies QC bead distributions in the FSC-SSC parameter space, allowing the system to maintain measurement precision across varying purity levels without manual intervention, thus eliminating time-consuming re-adjustment cycles.
Data Source
AI summary
The present application relates to a system or method for auto gating of QC base on population analysis. The system or method is particular useful for a sample processing instrument (for example, a flow cytometer or analyzer). The method comprise the following steps: I) providing QC beads used for testing the performance index of an equipment of interest; II) setting the equipment to collect the data of the QC beads; III) analyzing the collected data and calculating the gate position of QC beads based on the collected data; and VI) adjusting the acquisition parameters of the equipment based on the calculated gate position.