A grid algorithm for high throughput fitting of dose-response curve data.
A grid algorithm for high throughput fitting of dose-response curve data.
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DOI：
10.2174/1875397301004010057
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发表时间：
2010-10-21
期刊：
影响因子：
--
通讯作者：
Nguyen DT
中科院分区：
文献类型：
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作者：
Wang Y;Jadhav A;Southal N;Huang R;Nguyen DT
我们描述了一种新的算法，网格算法，以及相应的计算机程序，用于高通量拟合由四参数对称逻辑剂量响应模型描述的剂量响应曲线。网格算法在四维（参数）的网格中搜索所有点，并找到与最佳拟合相对应的最优点。使用模拟剂量响应曲线，我们检查了Grid程序在再现用于生成模拟数据的实际值方面的性能，并将其与用于语言和环境R的DRC包以及用于Microsoft Excel的XLfit插件进行了比较。网格程序具有鲁棒性，并且在有或无噪声的情况下都能一致地恢复完整和部分曲线的实际值。DRC和XLfit在没有噪声的数据上表现良好，但它们对噪声敏感，并且随着噪声的增加性能迅速下降。网格程序是自动化的，可扩展到数百万个剂量反应曲线，每CPU小时能够处理100,000个高通量筛选实验的剂量反应曲线。网格程序具有极大地提高大规模剂量-反应数据分析和早期药物发现过程的生产力的潜力，它也适用于化学、生物和医学科学中的许多其他曲线拟合问题。
We describe a novel algorithm, Grid algorithm, and the corresponding computer program for high throughput fitting of dose-response curves that are described by the four-parameter symmetric logistic dose-response model. The Grid algorithm searches through all points in a grid of four dimensions (parameters) and finds the optimum one that corresponds to the best fit. Using simulated dose-response curves, we examined the Grid program’s performance in reproducing the actual values that were used to generate the simulated data and compared it with the DRC package for the language and environment R and the XLfit add-in for Microsoft Excel. The Grid program was robust and consistently recovered the actual values for both complete and partial curves with or without noise. Both DRC and XLfit performed well on data without noise, but they were sensitive to and their performance degraded rapidly with increasing noise. The Grid program is automated and scalable to millions of dose-response curves, and it is able to process 100,000 dose-response curves from high throughput screening experiment per CPU hour. The Grid program has the potential of greatly increasing the productivity of large-scale dose-response data analysis and early drug discovery processes, and it is also applicable to many other curve fitting problems in chemical, biological, and medical sciences.