Evaluation of cDNA microarray data by multiple clones mapping to the same transcript.
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.
Wang
Dong
D
School of Life Science and Bioinformatics Centre, University of Electronic Science and Technology of China , Chengdu, 610054, People's Republic of China.
Wang
Chenguang
C
Zhang
Lin
L
Xiao
Hui
H
Shen
Xiaopei
X
Ren
Liping
L
Zhao
Wenyuan
W
Hong
Guini
G
Zhang
Yuannv
Y
Zhu
Jing
J
Zhang
Min
M
Yang
Da
D
Ma
Wencai
W
Guo
Zheng
Z
D019295:Computational Biology / Q000379:methods*; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*