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A Report on the Inter-Gene Correlations in cDNA Microarray Data Sets
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 Title & Authors
A Report on the Inter-Gene Correlations in cDNA Microarray Data Sets
Kim, Byung-Soo; Jang, Jee-Sun; Kim, Sang-Cheol; Lim, Jo-Han;
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A series of recent papers reported that the inter-gene correlations in Affymetrix microarray data sets were strong and long-ranged, and the assumption of independence or weak dependence among gene expression signals which was often employed without justification was in conflict with actual data. Qui et al. (2005) indicated that applying the nonparametric empirical Bayes method in which test statistics were pooled across genes for performing the statistical inference resulted in the large variance of the number of differentially expressed genes. Qui et al. (2005) attributed this effect to strong and long-ranged inter-gene correlations. Klebanov and Yakovlev (2007) demonstrated that the inter-gene correlations provided a rich source of information rather than being a nuisance in the statistical analysis and they developed, by transforming the original gene expression sequence, a sequence of independent random variables which they referred to as a -sequence. We note in this report using two cDNA microarray data sets experimented in this country that the strong and long-ranged inter-gene correlations were still valid in cDNA microarray data and also the -sequence of independence could be derived from the cDNA microarray data. This note suggests that the inter-gene correlations be considered in the future analysis of the cDNA microarray data sets.
cDNA microarray;nonparametric empirical Bayes method;correlation;independence;differential expression;
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당귀(當歸)가 다낭성난소증후군이 유발된 흰쥐 난소조직의 유전자 발현에 미치는 영향,류기준;조성희;

대한한방부인과학회지, 2011. vol.24. 3, pp.28-47
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