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A mathematical framework for examining whether a minimum number of chiasmata is required per metacentric chromosome or chromosome arm in human.

机译:一个数学框架,用于检查人类的每个中枢染色体或染色体臂是否需要最小数量的视镜。

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摘要

We introduce a piecewise linear regression called "hockey stick regression" to model the relationship between genetic and physical lengths of chromosomes in a genome. This piecewise linear regression is an extension of the two-parameter linear regression we proposed earlier [W. Li and J. Freudenberg, Two-parameter characterization of chromosome-scale recombination rate, Genome Res., 19 (2009) 2300-2307]. We use this, as well as the one-piece regression with a fixed y-intercept, to compare the two competing hypotheses concerning the minimum number of required chiasmata for meiosis: minimum one chiasma per chromosome (PC) and per chromosome arm (PA). Using statistical model selection and testing, we show that for human genome data, one-piece PC (PC1) is often in a statistical tie with two-piece PA model (PA2). If an upper bound for the segmentation point in two-piece regression is imposed, PC is usually the preferred model. This indicates that a presence of more than one chiasmata is rather caused by the relationship between chromosome size and chiasma formation than by cytogenetic constraints.
机译:我们引入称为“曲棍球杆回归”的分段线性回归,以对基因组中染色体的遗传长度和物理长度之间的关系进行建模。这种分段线性回归是我们先前提出的两参数线性回归的扩展。 Li和J. Freudenberg,染色体尺度重组率的两参数表征,Genome Res。,19(2009)2300-2307]。我们使用此方法以及固定y轴截距的单项回归来比较有关减数分裂所需最小视交叉数的两个相互竞争的假设:每个染色体(PC)和每个染色体臂(PA)至少一个视交叉。通过统计模型的选择和测试,我们表明,对于人类基因组数据,一件式PC(PC1)通常与两件式PA模型(PA2)处于统计联系。如果在两件式回归中对分割点施加上限,则PC通常是首选模型。这表明存在多于一个的chiasmata,而不是由于染色体大小和chiasma形成之间的关系,而不是由于细胞遗传学限制。

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