Frequency Difference Gating for Multi-Parameter Data Analysis
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Solution Overview
Problem
Current methods for analyzing large, multi-parameter data sets in particle analysis, such as flow cytometry, are limited by manual, time-consuming, and non-deterministic approaches, which hinder meaningful comparisons and lead to biased results, missing subtle differences in cell populations and phenotypes that are critical for understanding biological responses and diseases.
Innovation Solution
A computer-implemented method for visualizing differences between n-dimensional data sets using frequency difference gating, which adjusts thresholds and generates heat maps to identify regions with varying event frequencies, enabling more accurate and reproducible comparisons of cell populations across samples.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual analysis methods are used for particle data, then analysis can be performed with simple tools, but the analysis time is excessive and results are non-deterministic
Solution Approach 1:
The patent replaces manual mechanical analysis with automated computer-based frequency difference gating algorithms. The system automatically calculates frequency differences across multiple parameters and generates visualizations without human intervention, eliminating the time-consuming manual gating process while maintaining analytical accuracy.
Solution Approach 2:
The patent transforms the analysis approach by changing from manual parameter evaluation to automated multi-parameter frequency comparison. The system evaluates multiple parameters simultaneously using statistical algorithms, enabling rapid deterministic analysis of complex particle data sets that would be impractical to analyze manually.
2Measurement precision
If manual gating methods are used, then the analysis process is simple to implement, but subtle differences in cell populations are missed
Solution Approach 1:
The patent creates a universal automated analysis system that handles multiple parameters and cell population types simultaneously. The frequency difference gating algorithm works across diverse data sets and parameter combinations, providing consistent precise detection of subtle differences without requiring manual method adjustments for each case.
Solution Approach 2:
The patent introduces automated computational algorithms as intermediaries between raw particle data and analytical conclusions. The frequency difference gating system acts as a mediator that objectively processes multi-parameter data, eliminating human bias and detecting subtle population differences that manual analysis would miss.
3Loss of information
If traditional visualization methods are used, then the display is simple, but comparative analysis between samples is limited
Solution Approach 1:
The patent extends traditional 2D flow cytometry visualizations into multi-dimensional frequency difference space. By adding frequency difference as a new dimension and using color-coded heat maps to represent magnitude and direction of differences, the system preserves comprehensive information while enabling intuitive comparative analysis across multiple parameters and samples simultaneously.
Data Source
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AI summary
Some embodiments of the methods provided herein relate to sample analysis and particle characterization methods for large, multi-parameter data sets. Frequency difference gating compares at least two different data sets to identify regions in a multivariate space where a frequency of events from a first data set is different than a frequency of events from the second data set according to a defined threshold.