Spectral averaging with outlier rejection algorithms to increase identifications in top-down proteomics.

ABSTRACT: The identification of proteoforms by top-down proteomics requires both high quality fragmentation spectra and the neutral mass of the proteoform from which the fragments derive. Intact proteoform spectra can be highly complex and may include multiple overlapping proteoforms, as well as many isotopic peaks and charge states. The resulting lower signal-to-noise ratios for intact proteins complicates downstream analyses such as deconvolution. Averaging multiple scans is a common way to improve signal-to-noise, but mass spectrometry data contains artifacts unique to it that can degrade the quality of an averaged spectra. To overcome these limitations and increase signal-to-noise, we have implemented outlier rejection algorithms to remove outlier measurements efficiently and robustly in a set o

SUBMITTER: Carr AV 

PROVIDER: S-EPMC11216233 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature