Assessment of data processing to improve reliability of microarray experiments using genomic DNA reference.
BACKGROUND
Using genomic DNA as common reference in microarray experiments has recently been tested by different laboratories. Conflicting results have been reported with regard to the reliability of microarray results using this method. To explain it, we hypothesize that data processing is a critical element that impacts the data quality.


RESULTS
Microarray experiments were performed in a gamma-proteobacterium Shewanella oneidensis. Pair-wise comparison of three experimental conditions was obtained either with two labeled cDNA samples co-hybridized to the same array, or by employing Shewanella genomic DNA as a standard reference. Various data processing techniques were exploited to reduce the amount of inconsistency between both methods and the results were assessed. We discovered that data quality was significantly improved by imposing the constraint of minimal number of replicates, logarithmic transformation and random error analyses.


CONCLUSIONS
These findings demonstrate that data processing significantly influences data quality, which provides an explanation for the conflicting evaluation in the literature. This work could serve as a guideline for microarray data analysis using genomic DNA as a standard reference.
Yang
Yunfeng
Y
Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA. yang@ornl.gov
Zhu
Mengxia
M
Wu
Liyou
L
Zhou
Jizhong
J
D000704:Analysis of Variance; D019295:Computational Biology / Q000379:methods*; D004269:DNA, Bacterial / Q000235:genetics; D001330:Electronic Data Processing / Q000592:standards*; D020869:Gene Expression Profiling; D016680:Genome, Bacterial; D023281:Genomics / Q000379:methods*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D012015:Reference Standards; D012107:Research Design; D020592:Shewanella / Q000235:genetics
D004269:DNA, Bacterial