Variability assessment of LC-MS experiments and its application to experimental design and difference detection

Yi Zhao; Tsung Heng Tsai; Cristina Di Poto; Lewis K. Pannell; Mahlet G. Tadesse; Habtom W. Ressom

doi:10.1109/GENSIPS.2012.6507762

Variability assessment of LC-MS experiments and its application to experimental design and difference detection

Yi Zhao, Tsung Heng Tsai, Cristina Di Poto, Lewis K. Pannell, Mahlet G. Tadesse, Habtom W. Ressom

Pathology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In quantitative liquid chromatography-mass spectrometry (LC- MS) experiments, variability assessment helps improve experimental design and detect true differences in ion abundance. A peak-level mixed effects model is considered to estimate the variability due to heterogeneity of the biological samples, inconsistency in sample preparation, and instrument variation. We focus on determining the optimal number of replicates to achieve adequate statistical power. We perform two simulation studies to demonstrate important factors in replication assignment, sample size calculation and difference detection. The parameters of the simulation studies are derived based on analysis of an in-house LC-MS data set. Sensitivity and false discovery rate of the mixed effects model are compared to those of t-test and fixed effects model.

Original language	English (US)
Title of host publication	Proceedings 2012 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2012
Pages	195-198
Number of pages	4
DOIs	https://doi.org/10.1109/GENSIPS.2012.6507762
State	Published - 2012
Event	2012 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2012 - Washington, DC, United States Duration: Dec 2 2012 → Dec 4 2012

Publication series

Name	Proceedings - IEEE International Workshop on Genomic Signal Processing and Statistics
ISSN (Print)	2150-3001
ISSN (Electronic)	2150-301X

Other

Other	2012 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2012
Country/Territory	United States
City	Washington, DC
Period	12/2/12 → 12/4/12

Keywords

Assignment of replicates
Difference detection
Experimental design
Liquid chromatography-mass spectrometry (LC-MS)
Mixed effects model
Peak-level quantification
Quantitative proteomics
Restricted maximum likelihood (REML)
Sample size calculation

ASJC Scopus subject areas

Biochemistry, Genetics and Molecular Biology (miscellaneous)
Computational Theory and Mathematics
Signal Processing
Biomedical Engineering

Access to Document

10.1109/GENSIPS.2012.6507762

Cite this

Zhao, Y., Tsai, T. H., Di Poto, C., Pannell, L. K., Tadesse, M. G., & Ressom, H. W. (2012). Variability assessment of LC-MS experiments and its application to experimental design and difference detection. In Proceedings 2012 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2012 (pp. 195-198). Article 6507762 (Proceedings - IEEE International Workshop on Genomic Signal Processing and Statistics). https://doi.org/10.1109/GENSIPS.2012.6507762

Variability assessment of LC-MS experiments and its application to experimental design and difference detection. / Zhao, Yi; Tsai, Tsung Heng; Di Poto, Cristina et al.
Proceedings 2012 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2012. 2012. p. 195-198 6507762 (Proceedings - IEEE International Workshop on Genomic Signal Processing and Statistics).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Zhao, Y, Tsai, TH, Di Poto, C, Pannell, LK, Tadesse, MG & Ressom, HW 2012, Variability assessment of LC-MS experiments and its application to experimental design and difference detection. in Proceedings 2012 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2012., 6507762, Proceedings - IEEE International Workshop on Genomic Signal Processing and Statistics, pp. 195-198, 2012 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2012, Washington, DC, United States, 12/2/12. https://doi.org/10.1109/GENSIPS.2012.6507762

Zhao Y, Tsai TH, Di Poto C, Pannell LK, Tadesse MG, Ressom HW. Variability assessment of LC-MS experiments and its application to experimental design and difference detection. In Proceedings 2012 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2012. 2012. p. 195-198. 6507762. (Proceedings - IEEE International Workshop on Genomic Signal Processing and Statistics). doi: 10.1109/GENSIPS.2012.6507762

Zhao, Yi ; Tsai, Tsung Heng ; Di Poto, Cristina et al. / Variability assessment of LC-MS experiments and its application to experimental design and difference detection. Proceedings 2012 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2012. 2012. pp. 195-198 (Proceedings - IEEE International Workshop on Genomic Signal Processing and Statistics).

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abstract = "In quantitative liquid chromatography-mass spectrometry (LC- MS) experiments, variability assessment helps improve experimental design and detect true differences in ion abundance. A peak-level mixed effects model is considered to estimate the variability due to heterogeneity of the biological samples, inconsistency in sample preparation, and instrument variation. We focus on determining the optimal number of replicates to achieve adequate statistical power. We perform two simulation studies to demonstrate important factors in replication assignment, sample size calculation and difference detection. The parameters of the simulation studies are derived based on analysis of an in-house LC-MS data set. Sensitivity and false discovery rate of the mixed effects model are compared to those of t-test and fixed effects model.",

keywords = "Assignment of replicates, Difference detection, Experimental design, Liquid chromatography-mass spectrometry (LC-MS), Mixed effects model, Peak-level quantification, Quantitative proteomics, Restricted maximum likelihood (REML), Sample size calculation",

author = "Yi Zhao and Tsai, {Tsung Heng} and {Di Poto}, Cristina and Pannell, {Lewis K.} and Tadesse, {Mahlet G.} and Ressom, {Habtom W.}",

note = "Copyright: Copyright 2013 Elsevier B.V., All rights reserved.; 2012 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2012 ; Conference date: 02-12-2012 Through 04-12-2012",

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AU - Tadesse, Mahlet G.

AU - Ressom, Habtom W.

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AB - In quantitative liquid chromatography-mass spectrometry (LC- MS) experiments, variability assessment helps improve experimental design and detect true differences in ion abundance. A peak-level mixed effects model is considered to estimate the variability due to heterogeneity of the biological samples, inconsistency in sample preparation, and instrument variation. We focus on determining the optimal number of replicates to achieve adequate statistical power. We perform two simulation studies to demonstrate important factors in replication assignment, sample size calculation and difference detection. The parameters of the simulation studies are derived based on analysis of an in-house LC-MS data set. Sensitivity and false discovery rate of the mixed effects model are compared to those of t-test and fixed effects model.

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Variability assessment of LC-MS experiments and its application to experimental design and difference detection

Abstract

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Keywords

ASJC Scopus subject areas

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