TY - JOUR
T1 - Evaluation of cDNA microarray data by multiple clones mapping to the same transcript
AU - Wang, Dong
AU - Wang, Chenguang
AU - Zhang, Lin
AU - Xiao, Hui
AU - Shen, Xiaopei
AU - Ren, Liping
AU - Zhao, Wenyuan
AU - Hong, Guini
AU - Zhang, Yuannv
AU - Zhu, Jing
AU - Zhang, Min
AU - Yang, Da
AU - Ma, Wencai
AU - Guo, Zheng
PY - 2009/12/1
Y1 - 2009/12/1
N2 - 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.
AB - 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.
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U2 - 10.1089/omi.2009.0077
DO - 10.1089/omi.2009.0077
M3 - Article
C2 - 19715395
AN - SCOPUS:73149097935
SN - 1536-2310
VL - 13
SP - 493
EP - 499
JO - OMICS A Journal of Integrative Biology
JF - OMICS A Journal of Integrative Biology
IS - 6
ER -