
doi: 10.1021/pr700640a
pmid: 18173224
Mass spectrometry data from high-resolution time-of-flight instruments often contain a vast number of noninformative background-ion peaks whose signal is similar to that of peptide peaks. Consequently, seeking peptide signal in these spectra based on a signal-to-noise ratio will remove signal peaks as well as noise. This work characterizes the background as a precursor to seeking peptide-related features. Robust-regression methods are used to estimate distributions for null (background) peak intensities and locations. Defining signal peaks as outliers with respect to these distributions leads to more precision in detecting the isotopic envelope of peaks from low-abundance peptides in high-resolution spectra.
Data Interpretation, Statistical, Signal Processing, Computer-Assisted, Mass Spectrometry
Data Interpretation, Statistical, Signal Processing, Computer-Assisted, Mass Spectrometry
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