Evaluation of cDNA microarray data by multiple clones mapping to the same transcript

Dong Wang, Chenguang Wang, Lin Zhang, Hui Xiao, Xiaopei Shen, Liping Ren, Wenyuan Zhao, Guini Hong, Yuannv Zhang, Jing Zhu, Min Zhang, Da Yang, Wencai Ma, Zheng Guo

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Although novel technologies are rapidly emerging, the cDNA microarray data accumulated is still and will be an important source for bioinformatics and biological studies. Thus, the reliability and applicability of the cDNA microarray data warrants further evaluation. In cDNA microarrays, multiple clones are measured for a transcript, which can be exploited to evaluate the consistency of microarray data. We show that even for pairs of RCs, the average Pearson correlation coefficient of their measurements is not high. However, this low consistency could largely be explained by random noise signals for a fraction of unexpressed genes and/or low signal-to-noise ratios for low abundance transcripts. Encouragingly, a large fraction of inconsistent data will be filtered out in the procedure of selecting differentially expressed genes (DEGs). Therefore, although cDNA microarray data are of low consistency, applications based on DEGs selections could still reach correct biological results, especially at the functional modules level.

Original languageEnglish (US)
Pages (from-to)493-499
Number of pages7
JournalOMICS A Journal of Integrative Biology
Issue number6
StatePublished - Dec 1 2009
Externally publishedYes

ASJC Scopus subject areas

  • Biotechnology
  • Biochemistry
  • Molecular Medicine
  • Molecular Biology
  • Genetics


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