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Normalization Method for Transcriptional Studies of Heterogeneous Samples - Simultaneous Array Normalization and Identification of Equivalent Expression

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  • Qin Li-Xuan

    (Memorial Sloan-Kettering Cancer Center)

  • Satagopan Jaya M

    (Memorial Sloan-Kettering Cancer Center)

Abstract

Normalization is an important step in the analysis of microarray data of transcription profiles as systematic non-biological variations often arise from the multiple steps involved in any transcription profiling experiment. Existing methods for data normalization often assume that there are few or symmetric differential expression, but this assumption does not always hold. Alternatively, non-differentially expressed genes may be used for array normalization. However, it is unknown at the outset which genes are non-differentially expressed. In this paper we propose a hierarchical mixture model framework to simultaneously identify non-differentially expressed genes and normalize arrays using these genes. The Fisher's information matrix corresponding to array effects is derived, which provides useful intuition for guiding the choice of array normalization method. The operating characteristics of the proposed method are evaluated using simulated data. The simulations conducted under a wide range of parametric configurations suggest that the proposed method provides a useful alternative for array normalization. For example, the proposed method has better sensitivity than median normalization under modest prevalence of differentially expressed genes and when the magnitudes of over-expression and under-expression are not the same. Further, the proposed method has properties similar to median normalization when the prevalence of differentially expressed genes is very small. Empirical illustration of the proposed method is provided using a liposarcoma study from MSKCC to identify genes differentially expressed between normal fat tissue versus liposarcoma tissue samples.

Suggested Citation

  • Qin Li-Xuan & Satagopan Jaya M, 2009. "Normalization Method for Transcriptional Studies of Heterogeneous Samples - Simultaneous Array Normalization and Identification of Equivalent Expression," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-25, February.
    • Handle: RePEc:bpj:sagmbi:v:8:y:2009:i:1:n:10
    DOI: 10.2202/1544-6115.1339
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    References listed on IDEAS

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    1. Reilly C. & Wang C. & Rutherford M., 2003. "A Method for Normalizing Microarrays Using Genes That Are Not Differentially Expressed," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 868-878, January.
    2. Purdom Elizabeth & Holmes Susan P, 2005. "Error Distribution for Gene Expression Data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 4(1), pages 1-35, July.
    3. Danh V. Nguyen & A. Bulak Arpat & Naisyin Wang & Raymond J. Carroll, 2002. "DNA Microarray Experiments: Biological and Technological Aspects," Biometrics, The International Biometric Society, vol. 58(4), pages 701-717, December.
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