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Weighted Analysis of Paired Microarray Experiments

Author

Listed:
  • Kristiansson Erik

    (Chalmers University of Technology, first two authors contributed equally)

  • Sjögren Anders

    (Chalmers University of Technology, first two authors contributed equally)

  • Rudemo Mats

    (Chalmers University of Technology)

  • Nerman Olle

    (Chalmers University of Technology)

Abstract

In microarray experiments quality often varies, for example between samples and between arrays. The need for quality control is therefore strong. A statistical model and a corresponding analysis method is suggested for experiments with pairing, including designs with individuals observed before and after treatment and many experiments with two-colour spotted arrays. The model is of mixed type with some parameters estimated by an empirical Bayes method. Differences in quality are modelled by individual variances and correlations between repetitions. The method is applied to three real and several simulated datasets. Two of the real datasets are of Affymetrix type with patients profiled before and after treatment, and the third dataset is of two-colour spotted cDNA type. In all cases, the patients or arrays had different estimated variances, leading to distinctly unequal weights in the analysis. We suggest also plots which illustrate the variances and correlations that affect the weights computed by our analysis method. For simulated data the improvement relative to previously published methods without weighting is shown to be substantial.

Suggested Citation

  • Kristiansson Erik & Sjögren Anders & Rudemo Mats & Nerman Olle, 2005. "Weighted Analysis of Paired Microarray Experiments," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 4(1), pages 1-47, October.
    • Handle: RePEc:bpj:sagmbi:v:4:y:2005:i:1:n:30
    DOI: 10.2202/1544-6115.1160
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    Cited by:

    1. Lim Johan & Kim Jayoun & Kim Sang-cheol & Yu Donghyeon & Kim Kyunga & Kim Byung Soo, 2012. "Detection of Differentially Expressed Gene Sets in a Partially Paired Microarray Data Set," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(3), pages 1-30, February.

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