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arXiv 0909.3132q-bio.GNq-bio.PE
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偏相关分析表明GC含量、外显子密度和人类基因组中的重组率之间存在因果关系

Partial correlation analysis indicates causal relationships between GC-content, exon density and recombination rate in the human genome

Jan Freudengerb, Mingyi Wang, Yaning Yang, Wentian Li

摘要:

{ \bf背景}:已知几个特征与人类基因组中的GC含量相关,包括重组率、基因密度和到端粒的距离。然而,仅通过检验成对相关性,无法区分直接关联和间接关联,也无法区分因果关系。{ \bf结果}:我们使用偏相关来构建以下四个变量的部分有向图:GC含量,重组率,外显子密度和端粒距离。重组率和外显子密度无条件地不相关,但通过GC含量的调节而成负相关。该模式表明重组率和外显子密度是GC含量变化的两个独立原因的模型。{ \bf结论}:因果推理和图形模型是理解基因组进化和人类基因组等容线进化机制的有用方法。

英文摘要:

{\bf Background}: Several features are known to correlate with the GC-content in the human genome, including recombination rate, gene density and distance to telomere. However, by testing for pairwise correlation only, it is impossible to distinguish direct associations from indirect ones and to distinguish between causes and effects. {\bf Results}: We use partial correlations to construct partially directed graphs for the following four variables: GC-content, recombination rate, exon density and distance-to-telomere. Recombination rate and exon density are unconditionally uncorrelated, but become inversely correlated by conditioning on GC-content. This pattern indicates a model where recombination rate and exon density are two independent causes of GC-content variation. {\bf Conclusions}: Causal inference and graphical models are useful methods to understand genome evolution and the mechanisms of isochore evolution in the human genome.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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