Sliding windows deconvolution - BioPharma Finder Software - Sliding windows deconvolution - BioPharma Finder Software - BioPharma Finder Software

Sliding windows deconvolution is a new approach to identifying components in LC/MS data. This approach does not follow the typical progression of identifying peaks—that is, averaging the peaks over a specified retention time range and then deconvolving the average spectra. Instead, this method sequentially averages spectra over overlapping retention time windows, deconvolves the averaged spectra, and merges similar found masses to identify components.

You can use sliding windows deconvolution with both the Xtract algorithm and ReSpect algorithm by setting up the appropriate method parameters.

See Working with an intact mass processing method.

Among the three deconvolution methods (average over selected retention time, automatic peak detection, and sliding windows) for the Xtract and ReSpect algorithms in the BioPharma Finder application, the sliding windows method has several advantages:

• It avoids issues involving the identification of complicated or poorly defined chromatographic peaks associated with large molecules.
• It identifies and characterizes components that co-elute over overlapping retention time (RT) ranges.
• It produces a meaningful elution profile for each identified component.
• It greatly reduces the rate of false-positives (incorrectly identified components).

Using sliding windows deconvolution involves two steps: the sliding window step and the mass merge step.

1. During the sliding windows step:
2. A conventional sliding window is applied along a RT axis to generate a succession of time-averaged spectra.
3. Then, the average spectrum is deconvolved from each sliding window and the resulting components compiled into a list of member components. Each of these member components has five associated parameters: mass, start retention time, stop retention time, intensity, and a fitness score (for results from the ReSpect algorithm).



2. During the mass merge step:
3. (For ReSpect results only) Components with a quality score below the specified Quality Score threshold are discarded.
4. The list of member components compiled by the sliding windows step is sorted by mass.
5. A sliding window is applied along a user-defined mass axis to identify member components with similar masses (according to the user-defined Merge Tolerance parameter) and merge peaks associated with the same component.
6. Merged components that do not meet the user-defined Min. Number of Detected Intervals parameter are discarded.
7. For each of the remaining merged components, components that exceed the user-specified Maximum Retention Time Gap parameter are split into distinct components.
8. For more information on the user-defined parameters described above, see Working with an intact mass processing method.

The sliding window methods allows you to merge your data using either the Improved Merge Scheme or the conventional Legacy Merge Scheme. The Improved Merge Scheme offers the following advantages over the conventional scheme:

• It uses a more robust procedure to identify components.
• It provides greater sensitivity and reduced false-positive rates.
• It provides greater mass accuracy and is less affected by spectral noise.