Power of Deep Sequencing and Agilent Microarray for Gene Expression Profiling Study
Power of Deep Sequencing and Agilent Microarray for Gene Expression Profiling Study
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DOI：
10.1007/s12033-010-9249-6
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发表时间：
2010-06-01
影响因子：
2.6
通讯作者：
Zhang, Yong
中科院分区：
文献类型：
--
作者：
Feng, Lin;Liu, Hang;Zhang, Yong
新一代基于测序的数字基因表达标签分析（DGE）已被用于研究基因表达谱的变化。为了比较微阵列和DGE产生的数据的质量，我们用这些平台检查了体外细胞模型的基因表达谱。在本研究中，微阵列和DGE分别检测到17，362和15，938个基因，其中有13，221个重叠基因。两个平台的技术重复之间的相关系数> 0.99，检测方差< 9%。微阵列的动态范围固定在四个数量级，而DGE的动态范围是可扩展的。两个平台的一致性很高，特别是对于那些丰富的基因。对于丰度较低的基因，微阵列更难区分其表达变异。虽然微阵列可能最终被DGE或转录组测序（RNA-seq）在不久的将来取代，但微阵列仍然是稳定的，实用的，可行的，这可能是有用的大多数生物学研究人员。
Next-generation sequencing-based Digital Gene Expression tag profiling (DGE) has been used to study the changes in gene expression profiling. To compare the quality of the data generated by microarray and DGE, we examined the gene expression profiles of an in vitro cell model with these platforms. In this study, 17,362 and 15,938 genes were detected by microarray and DGE, respectively, with 13,221 overlapping genes. The correlation coefficients between the technical replicates were > 0.99 and the detection variance was < 9% for both platforms. The dynamic range of microarray was fixed with four orders of magnitude, whereas that of DGE was extendable. The consistency of the two platforms was high, especially for those abundant genes. It was more difficult for the microarray to distinguish the expression variation of less abundant genes. Although microarrays might be eventually replaced by DGE or transcriptome sequencing (RNA-seq) in the near future, microarrays are still stable, practical, and feasible, which may be useful for most biological researchers.