Open AccessEvaluating reproducibility and similarity of mass and intensity data in complex spectra—applications to tubulin
Author(s) -
Matthew T. Olson,
Paul S. Blank,
Dan L. Sackett,
Alfred L. Yergey
Publication year - 2008
Publication title -
journal of the american society for mass spectrometry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.961
H-Index - 127
eISSN - 1879-1123
pISSN - 1044-0305
DOI - 10.1016/j.jasms.2007.11.012
Subject(s) - similarity (geometry) , replicate , dot product , reproducibility , chemistry , spectral line , biological system , product (mathematics) , sampling (signal processing) , analytical chemistry (journal) , confidence interval , pattern recognition (psychology) , algorithm , statistics , artificial intelligence , mathematics , chromatography , computer science , physics , optics , biology , geometry , astronomy , detector , image (mathematics)
We present a data processing approach based on the spectral dot product for evaluating spectral similarity and reproducibility. The method introduces 95% confidence intervals on the spectral dot product to evaluate the strength of spectral correlation; it is the only calculation described to date that accounts for both the non-normal sampling distribution of the dot product and the number of peaks the spectra have in common. These measures of spectral similarity allow for the recursive generation of a consensus spectrum, which incorporates the most consistent features from statistically similar replicate spectra. Taking the spectral dot product and 95% confidence intervals between consensus spectra from different samples yields the similarity between these samples. Applying the data analysis scheme to replicates of brain tubulin CNBr peptides enables a robust comparison of tubulin isotype expression and post-translational modification patterns in rat and cow brains.