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However, most large expression datasets are too sparse to infer high statistical confidence gene relationships which are based on the estimate of a covariance matrix. 1 In addition, the networks generated de novo are often large, and do not facilitate prioritization of candidate genes and gene relationships for hypothesis based validation.
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In a 72 hpf, a very large expression is found in the foregut, suggesting that most of its cells express Pdu-sna2.
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In other words, diet-related genes exhibit larger expression divergence than most differentially expressed genes in liver.
To understand the patterns of gene expression and correlations between the 10 libraries from which ESTs were generated, the contigs generated in UG-III set were analyzed using the R Stekel statistical test [ 12] of IDEG.6 tool to identify the most significant expression and large differences in the abundances of ESTs in each contig.
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