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Robust Parametric and Semi-parametric Spot Fitting for Spot Array Images

机译:专用阵列图像的强大参数和半参数点拟合

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In this paper we address the problem of reliably fitting parametric and semi-parametric models to spots in high density spot array images obtained in gene expression experiments. The goal is to measure the amount of label bound to an array element. A lot of spots can be modelled accurately by a Gaussian shape. In order to deal with highly overlapping spots we use robust M-estimators. When the parametric method fails (which can be detected automatically) we use a novel, robust semi-parametric method which can handle spots of different shapes accurately. The introduced techniques are evaluated experimentally.
机译:在本文中,我们解决了在基因表达实验中获得的高密度点阵列图像中的参数和半参数模型可靠地拟合参数和半参数模型的问题。目标是测量绑定到数组元素的标签量。通过高斯形状可以准确地建模很多斑点。为了处理高度重叠的斑点,我们使用强大的M估计。当参数方法发生故障时(可以自动检测到),我们使用一种新颖的鲁棒半导体方法,该方法可以精确地处理不同形状的斑点。通过实验评估引入的技术。

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