Analysis of Variance: Evaluating Differential Protein Expression

Plant Breeding and Genomics April 08, 2013 Print Friendly and PDF

Author:

Shaun Broderick, The Ohio State University

This tutorial uses a case study in petunia to demonstrate ANOVA in SAS using the "PROC GLM" and "PROC VARCOMP" commands. Sample SAS code is provided. Using information from the ANOVA table and variance components output, an objective cut-off value based on least significant differences (LSD) for differential protein expression can be obtained. The tutorial is provided in Slideshare and pdf formats.

Introduction

Protein expression data from petunia flowers at different stages of flower senescence was analyzed using the "PROC GLM" and "PROC VARCOMP" commands in SAS to obtain an ANOVA table and variance components table. These outputs were used to determine an objective cut-off value for differential protein expression based on least significant differences (LSD).

References Cited

  • Bai, S., B. Willard, L. J. Chapin, M. T. Kinter, D. M. Francis, A. D. Stead, and M. L. Jones. 2010. Proteomic analysis of pollination-induced corolla senescence in petunia. Journal of Experimental Botany 61:1089-1109. (Available online at: http://dx.doi.org/10.1093/jxb/erp373) (verified 20 Oct 2011).
  • Kerr, M. K., M. Martin, and G. A. Churchill. 2000. Analysis of variance for gene expression microarray data. Journal of Computational Biology 7:819-837. (Available online at: http://dx.doi.org/10.1089/10665270050514954) (verified 20 Oct 2011).

Funding Statement

Development of this page was supported in part by the National Institute of Food and Agriculture (NIFA) Solanaceae Coordinated Agricultural Project, agreement 2009-85606-05673, administered by Michigan State University. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the United States Department of Agriculture.

 

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This work is supported by the USDA National Institute of Food and Agriculture, New Technologies for Ag Extension project.