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首页> 外文期刊>Journal of Bioinformatics and Computational Biology >A PRACTICAL QUESTION BASED ON CROSS-PLATFORM MICROARRAY DATA NORMALIZATION: ARE BOEC MORE LIKE LARGE VESSEL OR MICROVASCULAR ENDOTHELIAL CELLS OR NEITHER OF THEM?
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A PRACTICAL QUESTION BASED ON CROSS-PLATFORM MICROARRAY DATA NORMALIZATION: ARE BOEC MORE LIKE LARGE VESSEL OR MICROVASCULAR ENDOTHELIAL CELLS OR NEITHER OF THEM?

机译:一个基于跨平台微阵列数据归一化的实用问题:是比其他大型容器或微血管内皮细胞更适合它们吗?

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摘要

Since the available microarray data of BOEC (human blood outgrowth endothelial cells), large vessel, and microvascular endothelial cells were from two different platforms, a working cross-platform normalization method was needed to make these data comparable. With six HUVEC (human umbilical vein endothelial cells) samples hybridized on two-channel cDNA arrays and six HUVEC samples on Affymetrix arrays, 64 possible combinations of a three-step normalization procedure were investigated to search for the best normalization method, which was selected, based on two criteria measuring the extent to which expression profiles of biological samples of the same cell type arrayed on two platforms were indistinguishable. Next, three discriminative gene lists between the large vessel and the microvascular endothelial cells were achieved by SAM (significant analysis of microarrays), PAM (prediction analysis for microarrays), and a combination of SAM and PAM lists. The final discriminative gene list was selectedby SVM (support vector machine). Based on this discriminative gene list, SVM classification analysis with best tuning parameters and 10,000 times of validations showed that BOEC were far from large vessel cells, they either formed their own class, or fell into the microvascular class. Based on all the common genes between the two platforms, SVM analysis further confirmed this conclusion.
机译:由于BOEC(人血生长内皮细胞),大血管和微血管内皮细胞的可用微阵列数据来自两个不同的平台,因此需要一种有效的跨平台标准化方法来使这些数据具有可比性。通过在两个通道cDNA阵列上杂交六个HUVEC(人脐静脉内皮细胞)样品,在Affymetrix阵列上杂交六个HUVEC样品,研究了64种可能的三步归一化方法组合,以寻求最佳的归一化方法,基于两个标准,该标准测量了在两个平台上排列的相同细胞类型的生物学样品的表达谱在何种程度上无法区分。接下来,通过SAM(微阵列的显着分析),PAM(微阵列的预测分析)以及SAM和PAM列表的组合,获得了大血管和微血管内皮细胞之间的三个判别基因列表。通过SVM(支持向量机)选择最终的区分性基因清单。基于此区分基因列表,具有最佳调整参数和10,000次验证的SVM分类分析表明,BOEC远离大型血管细胞,它们要么形成了自己的类别,要么就属于微血管类别。基于两个平台之间的所有共同基因,SVM分析进一步证实了这一结论。

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