Mass Spectra Peak Identification via Two-Stage Filtering
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Solution Overview
Problem
Identifying peaks corresponding to the same physical ion in mass spectra across different concentrations of a chemical solution is challenging due to measurement errors in mass and intensity, leading to inaccurate identification and potential accumulation of contributions from different ions in the same bin, especially when dealing with dense sequences of peaks.
Innovation Solution
A method involving a two-stage filtering process on a computer, where the first stage uses a mass-intensity based proximity criterion to identify peaks generated by the same ion across different spectra, and the second stage applies a combined mass-proximity and concentration-intensity correlation criterion to refine the identification, resulting in virtual peaks that correspond to the same ion across varying concentrations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data binning technique is used to identify peaks corresponding to the same ion, then measurement errors are reduced, but peaks of different ions with similar masses are accumulated in the same bin
Solution Approach 1:
The method segments the peak identification process into two distinct stages: first stage uses mass-intensity proximity to group peaks, second stage uses concentration-intensity correlation to verify and refine the identification. This segmentation allows each stage to focus on specific criteria, improving overall accuracy while maintaining reliability.
Solution Approach 2:
The first stage performs preliminary grouping of peaks based on mass and intensity proximity before the second stage verifies these groupings using concentration correlation. This preliminary action creates initial candidate groups that are then refined, ensuring that final identifications are both precise and reliable.
2Measurement precision
If bin size is larger than measurement error to reduce error effects, then peaks of two or more ions with similar masses are accumulated in the same bin
Solution Approach 1:
The second stage uses concentration-intensity correlation as a feedback mechanism to verify whether peaks grouped in the first stage truly correspond to the same ion. If peaks from different ions are incorrectly grouped, the concentration correlation will be poor, allowing the method to identify and correct these errors, thus preventing loss of ion contribution information.
Solution Approach 2:
The method dynamically adjusts the identification criteria between two stages: first using static mass-intensity proximity, then using dynamic concentration correlation that adapts to the specific characteristics of each ion across different concentrations. This dynamic approach allows flexible handling of varying bin sizes and error conditions.
3Productivity
If mass spectrum contains dense sequence of peaks from organic molecule dissociation, then identification of peaks corresponding to the same ion becomes difficult, but comprehensive analysis of all ions is required
Solution Approach 1:
The method extracts the concentration-intensity correlation characteristic as a key identifier to distinguish peaks from the same ion among dense sequences of peaks. By focusing on this specific extracted feature, the method simplifies the identification process even when many ions are present, maintaining analysis completeness while reducing identification difficulty.
Data Source
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AI summary
A method, computer program and system to identify peaks generated by different physical ions in a solution including substances by analyzing mass and intensity coordinates of all peaks in a set of mass spectra measured with errors for a certain concentration c of the solution is here disclosed. The peaks in different mass spectra are associated to a same ion if they are sufficiently `close´ according to specific discrimination criteria that go beyond the proximity of mass values. A two stage process is applied, each stage consisting in applying the method to identify peaks in mass spectra. In stage 1, the method to identify peaks is applied on each set of mass spectra for each concentration. Resulting sequences of peaks, one peak in each spectrum, are associated to different ions. This output of stage 1 is converted into a set of virtual mass spectra having as virtual peaks, average peak coordinate values calculated on each sequence. The method to identify peaks is applied once on the virtual mass spectra and the resulting ion identification table refers to peak coordinates values associated to one ion for each concentration of the solution.