ExactDAS:一个精确的测试程序,用于检测微阵列实验中不同的选择性剪接。

IF 0.8 4区 数学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Tristan Mary-Huard, Florence Jaffrezic, Stéphane Robin
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引用次数: 0

摘要

本文的目的是提出一种测试程序,用于检测平铺阵列或外显子芯片数据的不同条件下的差异选择性剪接。虽然在混合模型框架中开发,但测试过程是精确的(避免了计算负担),并且适用于各种各样的对比,包括以前发表的一些对比。仿真研究验证了该方法的鲁棒性和性能。它对不同选择性剪接下的基因有很好的检测能力,甚至对5个生物复制和每个外显子4个探针都有很好的检测能力。该方法还可以通过精确的功率曲线对各种实验设计进行比较。这是通过配对和非配对实验的比较来说明的。该测试程序应用于基于外显子阵列的两个公开可用的癌症数据集,并显示出令人鼓舞的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ExactDAS: an exact test procedure for the detection of differential alternative splicing in microarray experiments.

The aim of this paper is to propose a test procedure for the detection of differential alternative splicing across conditions for tiling array or exon chip data. While developed in a mixed model framework, the test procedure is exact (avoiding computational burden) and applicable to a large variety of contrasts, including several previously published ones. A simulation study is presented to evaluate the robustness and performance of the method. It is found to have a good detection power of genes under differential alternative splicing, even for five biological replicates and four probes per exon. The methodology also enables the comparison of various experimental designs through exact power curves. This is illustrated with the comparison of paired and unpaired experiments. The test procedure was applied to two publicly available cancer data sets based on exon arrays, and showed promising results.

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来源期刊
Statistical Applications in Genetics and Molecular Biology
Statistical Applications in Genetics and Molecular Biology BIOCHEMISTRY & MOLECULAR BIOLOGY-MATHEMATICAL & COMPUTATIONAL BIOLOGY
自引率
11.10%
发文量
8
期刊介绍: Statistical Applications in Genetics and Molecular Biology seeks to publish significant research on the application of statistical ideas to problems arising from computational biology. The focus of the papers should be on the relevant statistical issues but should contain a succinct description of the relevant biological problem being considered. The range of topics is wide and will include topics such as linkage mapping, association studies, gene finding and sequence alignment, protein structure prediction, design and analysis of microarray data, molecular evolution and phylogenetic trees, DNA topology, and data base search strategies. Both original research and review articles will be warmly received.
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