Statistics and Its Interface
Volume 13 (2020)
Meta-analysis of peptides to detect protein significance
Pages: 465 – 474
Shotgun assays are widely used in biotechnologies to characterize large molecules, which are hard to be measured as a whole directly. For instance, in Liquid Chromatography–Mass Spectrometry (LC–MS) shotgun experiments, proteins in biological samples are digested into peptides, and then peptides are separated and measured. However, in proteomics study, investigators are usually interested in the performance of the whole proteins instead of those peptide fragments. In light of meta-analysis, we propose an adaptive thresholding method to select informative peptides, and combine peptide-level models to protein-level analysis. The meta-analysis procedure and modeling rationale can be adapted to data analysis of other types of shotgun assays.
neta-analysis, adaptive thresholding, shotgun technology
This work was supported by National Institutes of Health (NIH) Grant HG 000250 (to R.W.D) and NIH grant P41GM103493 (to R.D.S).
Received 28 April 2019
Accepted 1 April 2020
Published 31 July 2020