Severgnini Marco, Bicciato Silvio, Mangano Eleonora, Scarlatti Francesca, Mezzelani Alessandra, Mattioli Michela, Ghidoni Riccardo, Peano Clelia, Bonnal Raoul, Viti Federica, Milanesi Luciano, De Bellis Gianluca, Battaglia Cristina
Institute of Biomedical Technologies, National Research Council, Milan, Italy.
Anal Biochem. 2006 Jun 1;353(1):43-56. doi: 10.1016/j.ab.2006.03.023. Epub 2006 Apr 3.
Meta-analysis of microarray data is increasingly important, considering both the availability of multiple platforms using disparate technologies and the accumulation in public repositories of data sets from different laboratories. We addressed the issue of comparing gene expression profiles from two microarray platforms by devising a standardized investigative strategy. We tested this procedure by studying MDA-MB-231 cells, which undergo apoptosis on treatment with resveratrol. Gene expression profiles were obtained using high-density, short-oligonucleotide, single-color microarray platforms: GeneChip (Affymetrix) and CodeLink (Amersham). Interplatform analyses were carried out on 8414 common transcripts represented on both platforms, as identified by LocusLink ID, representing 70.8% and 88.6% of annotated GeneChip and CodeLink features, respectively. We identified 105 differentially expressed genes (DEGs) on CodeLink and 42 DEGs on GeneChip. Among them, only 9 DEGs were commonly identified by both platforms. Multiple analyses (BLAST alignment of probes with target sequences, gene ontology, literature mining, and quantitative real-time PCR) permitted us to investigate the factors contributing to the generation of platform-dependent results in single-color microarray experiments. An effective approach to cross-platform comparison involves microarrays of similar technologies, samples prepared by identical methods, and a standardized battery of bioinformatic and statistical analyses.
考虑到使用不同技术的多个平台的可用性以及来自不同实验室的数据集在公共存储库中的积累，微阵列数据的荟萃分析变得越来越重要。我们通过设计一种标准化的研究策略，解决了比较两个微阵列平台基因表达谱的问题。我们通过研究经白藜芦醇处理后发生凋亡的MDA-MB-231细胞来测试此程序。使用高密度、短寡核苷酸、单色微阵列平台获得基因表达谱：基因芯片（Affymetrix）和CodeLink（Amersham）。对两个平台上由LocusLink ID标识的8414个共同转录本进行了平台间分析，分别占注释的基因芯片和CodeLink特征的70.8%和88.6%。我们在CodeLink上鉴定出105个差异表达基因（DEG），在基因芯片上鉴定出42个DEG。其中，两个平台共同鉴定出的只有9个DEG。多种分析（探针与靶序列的BLAST比对、基因本体论、文献挖掘和定量实时PCR）使我们能够研究在单色微阵列实验中导致产生平台依赖性结果的因素。一种有效的跨平台比较方法涉及类似技术的微阵列、通过相同方法制备的样品以及一系列标准化的生物信息学和统计分析。
