Detection of Differentially Expressed Gene Sets in a Partially Paired Microarray Data Set

Lim Johan, Kim Jayoun, Kim Sang-cheol, Yu Donghyeon, Kim Kyunga and Kim Byung Soo
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Lim Johan: Seoul National University
Kim Jayoun: Yonsei University
Kim Sang-cheol: Yonsei University
Yu Donghyeon: Seoul National University
Kim Kyunga: Sookmyung Women’s University
Kim Byung Soo: Yonsei University

Statistical Applications in Genetics and Molecular Biology, 2012, vol. 11, issue 3, 30

Abstract: Partially paired data sets often occur in microarray experiments (Kim et al., 2005; Liu, Liang and Jang, 2006). Discussions of testing with partially paired data are found in the literature (Lin and Stivers 1974; Ekbohm, 1976; Bhoj, 1978). Bhoj (1978) initially proposed a test statistic that uses a convex combination of paired and unpaired t statistics. Kim et al. (2005) later proposed the t3 statistic, which is a linear combination of paired and unpaired t statistics, and then used it to detect differentially expressed (DE) genes in colorectal cancer (CRC) cDNA microarray data. In this paper, we extend Kim et al.’s t3 statistic to the Hotelling’s T2 type statistic Tp for detecting DE gene sets of size p. We employ Efron’s empirical null principle to incorporate inter-gene correlation in the estimation of the false discovery rate. Then, the proposed Tp statistic is applied to Kim et al’s CRC data to detect the DE gene sets of sizes p=2 and p=3. Our results show that for small p, particularly for p=2 and marginally for p=3, the proposed Tp statistic compliments the univariate procedure by detecting additional DE genes that were undetected in the univariate test procedure. We also conduct a simulation study to demonstrate that Efron’s empirical null principle is robust to the departure from the normal assumption.

Keywords: cDNA microarray; empirical null distribution; false discovery rate; Hotelling’s T2 statistic; multiple testing; partially paired data (search for similar items in EconPapers)
Date: 2012
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DOI: 10.1515/1544-6115.1610

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