Adiga P S, Bhomra A, Turri M G, Nicod A, Datta S R, Jeavons P, Mott R, Flint J
Psychiatric Genetics Group, Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Headington, Oxford OX3 7BN, UK.
Bioinformatics. 2001 Nov;17(11):1084-9. doi: 10.1093/bioinformatics/17.11.1084.
Automatic tools to speed up routine biological processes are very much sought after in bio-medical research. Much repetitive work in molecular biology, such as allele calling in genetic analysis, can be made semi-automatic or task specific automatic by using existing techniques from computer science and signal processing. Computerized analysis is reproducible and avoids various forms of human error. Semi-automatic techniques with an interactive check on the results speed up the analysis and reduce the error.
We have successfully implemented an image processing software package to automatically analyze agarose gel images of polymorphic DNA markers. We have obtained up to 90% accuracy for the classification of alleles in good quality images and up to 70% accuracy in average quality images. These results are obtained within a few seconds. Even after subsequent interactive checking to increase the accuracy of allele classification to 100%, the overall speed with which the data can be processed is greatly increased, compared to manual allele classification.
The IDL source code of the software is available on request from jonathan.flint@well.ox.ac.uk
在生物医学研究中,人们非常渴望能有自动工具来加速常规生物过程。分子生物学中的许多重复性工作,比如基因分析中的等位基因分型,通过运用计算机科学和信号处理的现有技术,可以实现半自动或特定任务的自动化。计算机化分析具有可重复性,并且能避免各种人为误差。带有对结果进行交互式检查的半自动技术能加快分析速度并减少误差。
我们成功实现了一个图像处理软件包,用于自动分析多态性DNA标记的琼脂糖凝胶图像。对于高质量图像中的等位基因分类,我们获得了高达90%的准确率,对于平均质量图像则达到了70%的准确率。这些结果在几秒钟内即可获得。即使在随后进行交互式检查以将等位基因分类的准确率提高到100%之后,与手动等位基因分类相比,数据处理的整体速度仍大幅提高。
可通过jonathan.flint@well.ox.ac.uk索取该软件的IDL源代码。