Quantitative study of single molecule location estimation techniques.
Quantitative study of single molecule location estimation techniques.
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DOI：
10.1364/oe.17.023352
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发表时间：
2009-12-21
期刊：
影响因子：
3.8
通讯作者：
Ober RJ
中科院分区：
文献类型：
--
作者：
Abraham AV;Ram S;Chao J;Ward ES;Ober RJ
从显微图像中估计单分子的位置是许多定量单分子数据分析技术中的关键步骤。单分子数据的拟合有不同的算法，特别是非线性最小二乘和最大似然估计。进行了比较，以评估这两种算法在不同的情况下的性能。我们的研究结果表明，这两个估计，平均而言，能够恢复在我们检查的所有情况下的单个分子的真实位置。然而，在没有建模不准确性和低噪声水平的情况下，最大似然估计比非线性最小二乘估计更准确，如通过其估计的标准偏差所测量的，并且对于被测试的成像和实验条件的集合达到最佳可能的准确度。虽然这两种算法都不是一贯的上级到其他建模不准确或误规范的存在下，最大似然算法出现作为一个强大的估计产生的结果与一致的精度跨越各种模型的不匹配和误规范。在高噪声水平下，相对于来自点源的信号，两种算法都没有明显的精度优势。还进行了比较，为两个定位精度的措施之前得出的。还讨论了具有用户友好的图形界面的软件包，用于单分子位置估计（EstimationTool）和定位精度计算（FandPLimitTool）的限制。
Estimating the location of single molecules from microscopy images is a key step in many quantitative single molecule data analysis techniques. Different algorithms have been advocated for the fitting of single molecule data, particularly the nonlinear least squares and maximum likelihood estimators. Comparisons were carried out to assess the performance of these two algorithms in different scenarios. Our results show that both estimators, on average, are able to recover the true location of the single molecule in all scenarios we examined. However, in the absence of modeling inaccuracies and low noise levels, the maximum likelihood estimator is more accurate than the nonlinear least squares estimator, as measured by the standard deviations of its estimates, and attains the best possible accuracy achievable for the sets of imaging and experimental conditions that were tested. Although neither algorithm is consistently superior to the other in the presence of modeling inaccuracies or misspecifications, the maximum likelihood algorithm emerges as a robust estimator producing results with consistent accuracy across various model mismatches and misspecifications. At high noise levels, relative to the signal from the point source, neither algorithm has a clear accuracy advantage over the other. Comparisons were also carried out for two localization accuracy measures derived previously. Software packages with user-friendly graphical interfaces developed for single molecule location estimation (EstimationTool) and limit of the localization accuracy calculations (FandPLimitTool) are also discussed.