TY - GEN
T1 - Biostatistical considerations of the use of genomic DNA reference in microarrays
AU - Yang, Yunfeng
AU - Zhu, Michelle M.
AU - Wu, Liyou
AU - Zhou, Jizhong
PY - 2007
Y1 - 2007
N2 - Using genomic DNA as common reference in microarray experiments has recently been tested by different laboratories (2, 3, 5, 7, 9, 20, 24-26). While some reported that experimental results of microarrays using genomic DNA reference conformed nicely to those obtained by cDNA: cDNA co-hybridization method, others acquired poor results. We hypothesized that these conflicting reports could be resolved by biostatistical analyses. To test it, microarray experiments were performed in a γ-proteobacterium Shewanella oneidensis. Pair-wise comparison of three experimental conditions was obtained either by direct cDNA: cDNA co-hybridization, or by indirect calculation through a Shewanella genomic DNA reference. Several major biostatistical techniques were exploited to reduce the amount of inconsistency between both methods and the results were assessed. We discovered that imposing the constraint of minimal number of replicates, logarithmic transformation and random error analyses significantly improved the data quality. These findings could potentially serve as guidelines for microarray data analysis using genomic DNA as reference.
AB - Using genomic DNA as common reference in microarray experiments has recently been tested by different laboratories (2, 3, 5, 7, 9, 20, 24-26). While some reported that experimental results of microarrays using genomic DNA reference conformed nicely to those obtained by cDNA: cDNA co-hybridization method, others acquired poor results. We hypothesized that these conflicting reports could be resolved by biostatistical analyses. To test it, microarray experiments were performed in a γ-proteobacterium Shewanella oneidensis. Pair-wise comparison of three experimental conditions was obtained either by direct cDNA: cDNA co-hybridization, or by indirect calculation through a Shewanella genomic DNA reference. Several major biostatistical techniques were exploited to reduce the amount of inconsistency between both methods and the results were assessed. We discovered that imposing the constraint of minimal number of replicates, logarithmic transformation and random error analyses significantly improved the data quality. These findings could potentially serve as guidelines for microarray data analysis using genomic DNA as reference.
UR - http://www.scopus.com/inward/record.url?scp=47649095704&partnerID=8YFLogxK
U2 - 10.1109/BIBE.2007.4375621
DO - 10.1109/BIBE.2007.4375621
M3 - Conference contribution
AN - SCOPUS:47649095704
SN - 1424415098
SN - 9781424415090
T3 - Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE
SP - 593
EP - 600
BT - Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE
T2 - 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE
Y2 - 14 January 2007 through 17 January 2007
ER -