Integrating probe-level expression changes across generations of Affymetrix arrays.

Integrating probe-level expression changes across generations of Affymetrix arrays.
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DOI:
10.1093/nar/gni193
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发表时间:
2005-12-14
影响因子:
14.9
通讯作者:
Aittokallio, T
Aittokallio, T
中科院分区:
生物学2区
文献类型:
--
作者:
Elo, LL;Lahti, L;Skottman, H;Kyläniemi, M;Lahesmaa, R;Aittokallio, T

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迫切需要能够对多个微阵列数据集进行综合分析的生物信息学方法。虽然以前的研究主要集中在不同平台内或不同平台之间基因表达水平的重复性,但我们提出了一种新的荟萃分析方法,该方法考虑了大量可用探针水平的信息,以结合不同研究的表达变化。我们首先证明,通过在探针水平确定表达变化,并考虑关于探针水平序列匹配的最新信息,而不是制造商提供的探针注释,可以显著提高不同Affymetrix阵列世代之间相对表达变化的可比性和差异表达基因的一致性。使用改进的探针级表达式变化估计,可以更有效地合并来自不同代Affymetrix阵列的数据。这将允许在设计和分析新实验时充分利用现有结果。
There is an urgent need for bioinformatic methods that allow integrative analysis of multiple microarray data sets. While previous studies have mainly concentrated on reproducibility of gene expression levels within or between different platforms, we propose a novel meta-analytic method that takes into account the vast amount of available probe-level information to combine the expression changes across different studies. We first show that the comparability of relative expression changes and the consistency of differentially expressed genes between different Affymetrix array generations can be considerably improved by determining the expression changes at the probe-level and by considering the latest information on probe-level sequence matching instead of the probe annotations provided by the manufacturer. With the improved probe-level expression change estimates, data from different generations of Affymetrix arrays can be combined more effectively. This will allow for the full exploitation of existing results when designing and analyzing new experiments.
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