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两种微阵列平台用于评估人类单核细胞和巨噬细胞中基因表达差异的性能比较。

Performance comparison of two microarray platforms to assess differential gene expression in human monocyte and macrophage cells.

作者信息

Maouche Seraya, Poirier Odette, Godefroy Tiphaine, Olaso Robert, Gut Ivo, Collet Jean-Phillipe, Montalescot Gilles, Cambien François

机构信息

INSERM UMR S525, Faculté de Médecine Pierre et Marie Curie, Université Paris VI, 91 Boulevard de l'Hôpital, Paris 75634 Cedex 13, France.

出版信息

BMC Genomics. 2008 Jun 25;9:302. doi: 10.1186/1471-2164-9-302.

Abstract

BACKGROUND

In this study we assessed the respective ability of Affymetrix and Illumina microarray methodologies to answer a relevant biological question, namely the change in gene expression between resting monocytes and macrophages derived from these monocytes. Five RNA samples for each type of cell were hybridized to the two platforms in parallel. In addition, a reference list of differentially expressed genes (DEG) was generated from a larger number of hybridizations (mRNA from 86 individuals) using the RNG/MRC two-color platform.

RESULTS

Our results show an important overlap of the Illumina and Affymetrix DEG lists. In addition, more than 70% of the genes in these lists were also present in the reference list. Overall the two platforms had very similar performance in terms of biological significance, evaluated by the presence in the DEG lists of an excess of genes belonging to Gene Ontology (GO) categories relevant for the biology of monocytes and macrophages. Our results support the conclusion of the MicroArray Quality Control (MAQC) project that the criteria used to constitute the DEG lists strongly influence the degree of concordance among platforms. However the importance of prioritizing genes by magnitude of effect (fold change) rather than statistical significance (p-value) to enhance cross-platform reproducibility recommended by the MAQC authors was not supported by our data.

CONCLUSION

Functional analysis based on GO enrichment demonstrates that the 2 compared technologies delivered very similar results and identified most of the relevant GO categories enriched in the reference list.

摘要

背景

在本研究中,我们评估了Affymetrix和Illumina微阵列技术回答一个相关生物学问题的各自能力,即静息单核细胞与源自这些单核细胞的巨噬细胞之间基因表达的变化。每种细胞类型的五个RNA样本被并行杂交到这两个平台上。此外,使用RNG/MRC双色平台,通过大量杂交(来自86个个体的mRNA)生成了差异表达基因(DEG)的参考列表。

结果

我们的结果显示Illumina和Affymetrix的DEG列表有重要重叠。此外,这些列表中超过70%的基因也出现在参考列表中。总体而言,就生物学意义而言,这两个平台的表现非常相似,这通过DEG列表中存在过量属于与单核细胞和巨噬细胞生物学相关的基因本体(GO)类别的基因来评估。我们的结果支持微阵列质量控制(MAQC)项目的结论,即用于构成DEG列表的标准强烈影响平台之间的一致性程度。然而,我们的数据不支持MAQC作者推荐的按效应大小(倍数变化)而非统计显著性(p值)对基因进行优先级排序以提高跨平台可重复性的重要性。

结论

基于GO富集的功能分析表明,所比较的这两种技术产生了非常相似的结果,并识别出参考列表中富集的大多数相关GO类别。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d68b/2464609/50556581c96c/1471-2164-9-302-1.jpg

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