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首页> 外文期刊>BMC Bioinformatics >A normalization strategy applied to HiCEP (an AFLP-based expression profiling) analysis: Toward the strict alignment of valid fragments across electrophoretic patterns
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A normalization strategy applied to HiCEP (an AFLP-based expression profiling) analysis: Toward the strict alignment of valid fragments across electrophoretic patterns

机译:应用于HiCEP(基于AFLP的表达谱)分析的归一化策略:跨电泳模式对有效片段进行严格比对

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摘要

Background Gene expression analysis based on comparison of electrophoretic patterns is strongly dependent on the accuracy of DNA fragment sizing. The current normalization strategy based on molecular weight markers has limited accuracy because marker peaks are often masked by intense peaks nearby. Cumulative errors in fragment lengths cause problems in the alignment of same-length fragments across different electropherograms, especially for small fragments (Results Here we describe a method for the normalization of a set of time-course electrophoretic data to be compared. The method uses Gaussian curves fitted to the complex peak mixtures in each electropherogram. It searches for target ranges for which patterns are dissimilar to the other patterns (called "dissimilar ranges") and for references (a kind of mean or typical pattern) in the set of resultant approximate patterns. It then constructs the optimal normalized pattern whose correlation coefficient against the reference in the range achieves the highest value among various combinations of candidates. We applied the procedure to time-course electrophoretic data produced by HiCEP, an AFLP-based expression profiling method which can detect a slight expression change in DNA fragments. We obtained dissimilar ranges whose electrophoretic patterns were obviously different from the reference and as expected, most of the fragments in the detected ranges were short (Conclusion The normalization strategy presented here demonstrates the importance of pre-processing before electrophoretic signal comparison, and we anticipate its usefulness especially for temporal expression analysis by the electrophoretic method.
机译:背景基于电泳图谱比较的基因表达分析在很大程度上取决于DNA片段大小的准​​确性。当前基于分子量标记的归一化策略准确性有限,因为标记峰经常被附近的强峰掩盖。片段长度的累积误差会导致不同电泳图上的相同长度片段的对齐出现问题,尤其是对于小片段(结果,在此,我们描述了一种标准化要比较的时程电泳数据集的方法。该方法使用高斯方法拟合每个电泳图中复杂峰混合物的曲线,在结果近似值集中搜索目标模式与其他模式不同的目标范围(称为“不同范围”)和参考(一种平均或典型模式)然后构建最优的归一化模式,该模式与候选值的相关系数在该范围内的各种候选组合中达到最高值,并将此程序应用于基于HiLPP的基于AFLP的表达谱分析方法产生的时程电泳数据。可以检测到DNA片段中的微小表达变化。色谱模式与参考明显不同,并且如预期的那样,检测范围内的大多数片段都很短(结论此处提出的归一化策略证明了电泳信号比较之前进行预处理的重要性,并且我们预计其有用性,特别是对于时间表达)电泳法分析。

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