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首页> 外文期刊>International Journal of Biomedical Science >Comparison of Two Methods for Detecting Alternative Splice Variants Using GeneChip® Exon Arrays
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Comparison of Two Methods for Detecting Alternative Splice Variants Using GeneChip® Exon Arrays

机译：使用GeneChip®外显子阵列检测替代剪接变体的两种方法的比较

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The Affymetrix GeneChip Exon Array can be used to detect alternative splice variants. Microarray Detection of Alternative Splicing (MIDAS) and Partek® Genomics Suite (Partek® GS) are among the most popular analytical methods used to analyze exon array data. While both methods utilize statistical significance for testing, MIDAS and Partek® GS could produce somewhat different results due to different underlying assumptions. Comparing MIDAS and Partek® GS is quite difficult due to their substantially different mathematical formulations and assumptions regarding alternative splice variants. For meaningful comparison, we have used the previously published generalized probe model (GPM) which encompasses both MIDAS and Partek® GS under different assumptions. We analyzed a colon cancer exon array data set using MIDAS, Partek® GS and GPM. MIDAS and Partek® GS produced quite different sets of genes that are considered to have alternative splice variants. Further, we found that GPM produced results similar to MIDAS as well as to Partek® GS under their respective assumptions. Within the GPM, we show how discoveries relating to alternative variants can be quite different due to different assumptions. MIDAS focuses on relative changes in expression values across different exons within genes and tends to be robust but less efficient. Partek® GS, however, uses absolute expression values of individual exons within genes and tends to be more efficient but more sensitive to the presence of outliers. From our observations, we conclude that MIDAS and Partek® GS produce complementary results, and discoveries from both analyses should be considered.
机译：Affymetrix GeneChip外显子阵列可用于检测其他剪接变体。替代剪接的微阵列检测（MIDAS）和Partek®基因组学套件（Partek®GS）是用于分析外显子阵列数据的最受欢迎的分析方法。尽管两种方法都利用统计意义进行测试，但由于不同的基本假设，MIDAS和Partek®GS可能会产生一些不同的结果。由于MIDAS和Partek®GS的数学公式和有关替代剪接变体的假设存在很大差异，因此比较它们非常困难。为了进行有意义的比较，我们使用了先前发布的广义探针模型（GPM），该模型涵盖了MIDAS和Partek®GS在不同假设下的情况。我们使用MIDAS，Partek®GS和GPM分析了结肠癌外显子阵列数据集。 MIDAS和Partek®GS产生了完全不同的基因集，这些基因被认为具有其他剪接变体。此外，我们发现，在各自的假设下，GPM产生的结果类似于MIDAS以及Partek®GS。在GPM中，我们展示了由于不同的假设，与替代变体相关的发现如何大不相同。 MIDAS着眼于基因内不同外显子的表达值的相对变化，并且倾向于鲁棒但效率较低。但是，Partek®GS使用基因内单个外显子的绝对表达值，并且往往更有效，但对异常值的存在更加敏感。根据我们的观察，我们得出结论，MIDAS和Partek®GS可以产生互补的结果，应考虑两种分析的发现。

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