Metabolomic Data Analysis via Profile and Orthogonal Plots
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Solution Overview
Problem
Conventional metabolomic data analysis techniques face challenges in efficiently analyzing and consolidating spectrometry data across multiple samples, leading to inaccuracies in identifying and quantifying metabolites due to file-based methods that require large computational resources, lack data consistency, and fail to account for subtle changes across sample populations.
Innovation Solution
A method and apparatus for analyzing data from a component separation and mass spectrometer system, which involves forming profile plots and orthogonal plots to identify and quantify intensity peaks, allowing for subjective evaluation and alignment of data across samples, thereby improving the accuracy and consistency of metabolite identification and quantification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If file-based methods are used to store and analyze spectrometry data for each sample individually, then data can be organized and accessed separately, but large amounts of computing power and memory capacity are required, and data consistency across multiple samples is poor
Solution Approach 1:
The patent combines multiple sample data files into a single consolidated data structure that stores spectrometry data from multiple samples together. This merging approach eliminates the need to handle numerous individual files, reducing computational overhead and improving data consistency across samples while maintaining easy access to individual sample information through the unified structure.
2Productivity
If conventional file-based analysis methods are used, then individual sample data can be processed independently, but the analysis consumes large amounts of time and computational power
Solution Approach 1:
The patent performs preliminary consolidation of spectrometry data from multiple samples into a unified data structure before analysis. By pre-organizing the data in this manner, the system eliminates the need for repeated file loading and processing operations during analysis, significantly reducing computational time and power consumption while maintaining the ability to analyze individual samples when needed.
3Measurement precision
If file-based data handling is used, then each sample can be analyzed independently, but subtle changes in metabolite composition across sample populations are not readily detectable
Solution Approach 1:
The patent merges spectrometry data from multiple samples into a consolidated data structure that enables simultaneous viewing and comparison across the entire sample population. This combination allows analysts to detect subtle metabolite composition changes that would be invisible when examining individual samples in isolation, while still preserving the ability to analyze specific samples independently when required.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables more accurate and efficient analysis of metabolomic data across multiple samples, reducing computational burdens and enhancing data consistency, allowing for better identification and quantification of metabolites, and facilitating the detection of subtle changes within sample populations.
Implementation Method 1
component separation and mass spectrometer system
Implementation Method 2
mass spectrometer system
Data Source
AI summary
A method, apparatus, and computer-readable storage medium for analyzing sample data from a component separation/mass spectrometer system. A profile plot is formed for each sample, each having retention time and intensity axes, the intensity being represented as a function of retention time for a selected sample ion mass. An intensity peak arrangement, including at least one identifying peak, each having a peak range and characteristic intensity, is identified for a selected ion in the profile plot for each sample. An orthogonal plot, corresponding to the profile plot, for each sample is formed, extending along the retention time axis perpendicularly to the intensity axis. The characteristic intensity of each of the at least one identifying peak is represented on the retention time axis of the orthogonal plot with gradated indicia.