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Exploring the Link Between Gene Expression and Protein Binding by Integrating mRNA Microarray and ChIP-Seq Data

机译:通过整合mRNA微阵列和ChIP-Seq数据探索基因表达与蛋白质结合之间的联系

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ChIP-sequencing experiments are routinely used to study genome-wide chromatin marks. Due to the high-cost and complexity associated with this technology, it is of great interest to investigate whether the low-cost option of microarray experiments can be used in combination with ChIP-seq experiments. Most integrative analyses do not consider important features of ChIP-seq data, such as spatial dependencies and ChIP-efficiencies. In this paper, we address these issues by applying a Markov random field model to ChIP-seq data on the protein Brd4, for which both ChIP-seq and microarray data are available on the same biological conditions. We investigate the correlation between the enrichment probabilities around transcription start sites, estimated by the Markov model, and microarray gene expression values. Our preliminary results suggest that binding of the protein is associated with lower gene expression, but differential binding across different conditions does not show an association with differential expression of the associated genes.
机译:通常使用ChIP测序实验来研究全基因组的染色质标记。由于与该技术相关的高成本和复杂性,研究微阵列实验的低成本选择是否可以与ChIP-seq实验结合使用非常重要。大多数集成分析都没有考虑ChIP-seq数据的重要特征,例如空间依赖性和ChIP效率。在本文中,我们通过对蛋白质Brd4的ChIP-seq数据应用Markov随机场模型来解决这些问题,在相同的生物学条件下,ChIP-seq和微阵列数据均可用。我们调查了由马尔可夫模型估计的转录起始位点附近的富集概率与微阵列基因表达值之间的相关性。我们的初步结果表明,蛋白质的结合与较低的基因表达有关,但在不同条件下的差异结合并未显示与相关基因的差异表达有关。

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