A Population-Size Model for Protein Spot Detection in Proteomic Studies

Chang Xuan Mao (), Sining Chen () and Yitong Yang ()
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Chang Xuan Mao: Shanghai University of Finance and Economics
Sining Chen: Bell Labs
Yitong Yang: Shanghai University of Finance and Economics

Journal of Agricultural, Biological and Environmental Statistics, 2016, vol. 21, issue 1, No 10, 170-180

Abstract: Abstract In proteomic studies, a population of proteins are often examined on a gel using a technique called two-dimensional gel eletrophoresis. The technique separates the protein population into individual protein spots on a two-dimensional gel by isoelectric charge and molecular weight. The resulting gel images are then processed by a software system for spot detection and subsequent analysis. The performance of a spot-detection program is evaluated by the total number of spots that are detected. A popular spot-detection program uses the “master–slave” approach, where all spots on “slave images” are subsets of the spots on the “master image.” We argue that this approach potentially misses a large proportion of proteins and propose a model that quantifies the lack of performance. We provide nonparametric estimators for the protein population size and the expected number of proteins to be detected if a “fusion-gel” approach was used. Using the data from a rat liver proteome study, we estimate that more than half of the protein population is missed by the master–slave approach.

Keywords: Binomial mixture; Capture–recapture; Lower bounds; Nonidentifiability (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s13253-015-0221-6

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