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      A Bayesian missing value estimation method for gene expression profile data

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          Abstract

          Gene expression profile analyses have been used in numerous studies covering a broad range of areas in biology. When unreliable measurements are excluded, missing values are introduced in gene expression profiles. Although existing multivariate analysis methods have difficulty with the treatment of missing values, this problem has received little attention. There are many options for dealing with missing values, each of which reaches drastically different results. Ignoring missing values is the simplest method and is frequently applied. This approach, however, has its flaws. In this article, we propose an estimation method for missing values, which is based on Bayesian principal component analysis (BPCA). Although the methodology that a probabilistic model and latent variables are estimated simultaneously within the framework of Bayes inference is not new in principle, actual BPCA implementation that makes it possible to estimate arbitrary missing variables is new in terms of statistical methodology. When applied to DNA microarray data from various experimental conditions, the BPCA method exhibited markedly better estimation ability than other recently proposed methods, such as singular value decomposition and K-nearest neighbors. While the estimation performance of existing methods depends on model parameters whose determination is difficult, our BPCA method is free from this difficulty. Accordingly, the BPCA method provides accurate and convenient estimation for missing values. The software is available at http://hawaii.aist-nara.ac.jp/~shige-o/tools/.

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          Author and article information

          Journal
          Bioinformatics
          Bioinformatics
          Oxford University Press (OUP)
          1367-4803
          1460-2059
          November 01 2003
          October 31 2003
          November 01 2003
          : 19
          : 16
          : 2088-2096
          Article
          10.1093/bioinformatics/btg287
          14594714
          © 2003

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