Computational protein profile similarity screening for quantitative mass spectrometry experiments

Kirchner, M., Renard, B. Y., Kothe, U., Pappin, D. J., Hamprecht, F. A., Steen, H., Steen, J. A. J. (2010) Computational protein profile similarity screening for quantitative mass spectrometry experiments. Bioinformatics, 26 (1). pp. 77-83. ISSN 1367-4803

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URL: https://www.ncbi.nlm.nih.gov/pubmed/19861354
DOI: 10.1093/bioinformatics/btp607

Abstract

Motivation: The qualitative and quantitative characterization of protein abundance profiles over a series of time points or a set of environmental conditions is becoming increasingly important. Using isobaric mass tagging experiments, mass spectrometry-based quantitative proteomics deliver accurate peptide abundance profiles for relative quantitation. Associated data analysis workflows need to provide tailored statistical treatment that (i) takes the correlation structure of the normalized peptide abundance profiles into account and (ii) allows inference of protein-level similarity. We introduce a suitable distance measure for relative abundance profiles, derive a statistical test for equality and propose a protein-level representation of peptide-level measurements. This yields a workflow that delivers a similarity ranking of protein abundance profiles with respect to a defined reference. All procedures have in common that they operate based on the true correlation structure that underlies the measurements. This optimizes power and delivers more intuitive and efficient results than existing methods that do not take these circumstances into account. Results: We use protein profile similarity screening to identify candidate proteins whose abundances are post-transcriptionally controlled by the Anaphase Promoting Complex/Cyclosome (APC/C), a specific E3 ubiquitin ligase that is a master regulator of the cell cycle. Results are compared with an established protein correlation profiling method. The proposed procedure yields a 50.9-fold enrichment of co-regulated protein candidates and a 2.5-fold improvement over the previous method.

Item Type: Paper
Uncontrolled Keywords: TANDEM AFFINITY PURIFICATION COMPOSITIONAL DATA STATISTICAL-ANALYSIS COMPLEX PROTEOMICS PRC1
Subjects: bioinformatics > computational biology
Investigative techniques and equipment > spectroscopy > mass spectrometry
CSHL Authors:
Communities: CSHL labs > Pappin lab
Depositing User: CSHL Librarian
Date Deposited: 04 Oct 2011 13:44
Last Modified: 24 Feb 2017 16:13
Related URLs:
URI: http://repository.cshl.edu/id/eprint/15454

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