点阵图像的鲁棒参数和半参数点拟合。

N Brändle, H Y Chen, H Bischof, H Lapp
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引用次数: 0

摘要

本文解决了基因表达实验中高密度斑点阵列图像中斑点的参数和半参数模型的可靠拟合问题。目标是测量绑定到数组元素的标签的数量。许多点可以用高斯形状精确地建模。为了处理高度重叠的点,我们使用了稳健的m估计量。当参数方法失效时(可以自动检测),我们采用了一种新颖的、鲁棒的半参数方法,可以准确地处理不同形状的斑点。对所介绍的技术进行了实验评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust parametric and semi-parametric spot fitting for spot array images.

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.

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