2016/06/29 by Alexia Kakourou, Werner Vach, Kakourou, Alexia +3
Biochemistry, Genetics and Molecular Biology · Chemistry · #Advanced Proteomics Techniques and Applications #FOS: Computer and information sciences #Mass Spectrometry Techniques and Applications #Metabolomics and Mass Spectrometry Studies #Methodology (stat.ME)
paper · pdf · doi:10.48550/arxiv.1606.09123
openalex publication_date 2016/06/29 · openalex created_date 2022/10/06 · openalex updated_date 2026/07/28
Despite the recent advances in mass spectrometry (MS), summarizing and\nanalyzing high-throughput mass-spectrometry data remains a challenging task.\nThis is, on the one hand, due to the complexity of the spectral signal which is\nmeasured, and on the other, due to the limit of detection (LOD). The LOD is\nrelated to the limitation of instruments in measuring markers at a relatively\nlow level. As a consequence, the outcome data set from the quantification step\nof proteomic analysis often consists of a reduced list of peaks where any peak\nintensities below the detection limit threshold are reported as missings. In\nthis work, we propose the use of censored data methodology to handle spectral\nmeasurements within the presence of LOD, recognizing that those have been\ncensored due to left-censoring mechanisms on low-abundance proteins. We apply\nthis approach to the particular problem of calibrating prediction rules through\nprior estimation of the average isotope expression in MALDI-FTICR\nmass-spectrometry data, collected in the context of a pancreatic cancer\ncase-control study. Our idea is to replace the set of incomplete spectral\nmeasurements with the average intensity estimates and use those as new input to\na prediction model. We evaluate the proposed methods, with respect to their\npredictive ability, by comparing their performance with the one achieved using\nthe complete information as well as alternative/competitive methods to deal\nwith the LOD.\n