title: Optimization of Statistical Methods Impact on Quantitative Proteomics Data.
abstract: As tools for quantitative label-free mass spectrometry (MS) rapidly develop, a consensus about the best practices is not apparent. In the work described here we compared popular statistical methods for detecting differential protein expression from quantitative MS data using both controlled experiments with known quantitative differences for specific proteins used as standards as well as "real" experiments where differences in protein abundance are not known a priori. Our results suggest that data-driven reproducibility-optimization can consistently produce reliable differential expression rankings for label-free proteome tools and are straightforward in their application.
authors: Turku Centre for Biotechnology, University of Turku and Åbo Akademi University , Tykistökatu 6, FI-20520 Turku, Finland.|Department of Mathematics and Statistics, University of Turku , FI-20014 Turku, Finland.
authors: Anna
authors: A
authors: Pursiheimo
authors: Turku Centre for Biotechnology, University of Turku and Åbo Akademi University , Tykistökatu 6, FI-20520 Turku, Finland.
authors: Anni P
authors: AP
authors: Vehmas
authors: Turku Centre for Biotechnology, University of Turku and Åbo Akademi University , Tykistökatu 6, FI-20520 Turku, Finland.
authors: Saira
authors: S
authors: Afzal
authors: Turku Centre for Biotechnology, University of Turku and Åbo Akademi University , Tykistökatu 6, FI-20520 Turku, Finland.|Department of Information Technology, University of Turku , FI-20014 Turku, Finland.
authors: Tomi
authors: T
authors: Suomi
authors: Turku Centre for Biotechnology, University of Turku and Åbo Akademi University , Tykistökatu 6, FI-20520 Turku, Finland.
authors: Thaman
authors: T
authors: Chand
authors: Department of Physiology and Turku Center for Disease Modeling, Institute of Biomedicine, University of Turku , Kiinamyllynkatu 10, FI-20520 Turku, Finland.
authors: Leena
authors: L
authors: Strauss
authors: Department of Physiology and Turku Center for Disease Modeling, Institute of Biomedicine, University of Turku , Kiinamyllynkatu 10, FI-20520 Turku, Finland.
authors: Matti
authors: M
authors: Poutanen
authors: Turku Centre for Biotechnology, University of Turku and Åbo Akademi University , Tykistökatu 6, FI-20520 Turku, Finland.
authors: Anne
authors: A
authors: Rokka
authors: Turku Centre for Biotechnology, University of Turku and Åbo Akademi University , Tykistökatu 6, FI-20520 Turku, Finland.|Van't Hoff Institute for Molecular Sciences, University of Amsterdam , P.O. Box 94157, 1090 GD Amsterdam, The Netherlands.
authors: Garry L
authors: GL
authors: Corthals
authors: Turku Centre for Biotechnology, University of Turku and Åbo Akademi University , Tykistökatu 6, FI-20520 Turku, Finland.|Department of Mathematics and Statistics, University of Turku , FI-20014 Turku, Finland.
authors: Laura L
authors: LL
authors: Elo
mesh_terms: D000465:Algorithms; D000818:Animals; D003627:Data Interpretation, Statistical; D030562:Databases, Protein; D066264:Datasets as Topic; D006801:Humans; D008099:Liver / Q000737:chemistry / Q000378:metabolism; D008297:Male; D051379:Mice; D008822:Mice, Transgenic; D010446:Peptide Fragments / Q000032:analysis*; D020543:Proteome / Q000302:isolation & purification*; D040901:Proteomics / Q000706:statistics & numerical data*; D015203:Reproducibility of Results; D012441:Saccharomyces cerevisiae / Q000737:chemistry / Q000378:metabolism; D012984:Software; D053719:Tandem Mass Spectrometry / Q000706:statistics & numerical data*; D014357:Trypsin / Q000737:chemistry
chemical_list: D010446:Peptide Fragments; D020543:Proteome; D014357:Trypsin
keywords: ROTS; label-free mass spectrometry; proteomics; quantitative analysis; reproducibility; statistical methods