Wagih Omar, Parts Leopold
European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK.
G3 (Bethesda). 2014 Mar 20;4(3):547-52. doi: 10.1534/g3.113.009431.
Colony-based screens that quantify the fitness of clonal populations on solid agar plates are perhaps the most important source of genome-scale functional information in microorganisms. The images of ordered arrays of mutants produced by such experiments can be difficult to process because of laboratory-specific plate features, morphed colonies, plate edges, noise, and other artifacts. Most of the tools developed to address this problem are optimized to handle a single setup and do not work out of the box in other settings. We present gitter, an image analysis tool for robust and accurate processing of images from colony-based screens. gitter works by first finding the grid of colonies from a preprocessed image and then locating the bounds of each colony separately. We show that gitter produces comparable colony sizes to other tools in simple cases but outperforms them by being able to handle a wider variety of screens and more accurately quantify colony sizes from difficult images. gitter is freely available as an R package from http://cran.r-project.org/web/packages/gitter under the LGPL. Tutorials and demos can be found at http://omarwagih.github.io/gitter.
基于菌落的筛选方法可量化克隆群体在固体琼脂平板上的适应性,这可能是微生物基因组规模功能信息的最重要来源。由于特定实验室的平板特征、变形的菌落、平板边缘、噪声和其他伪像,此类实验产生的突变体有序阵列图像可能难以处理。为解决此问题而开发的大多数工具都针对单一设置进行了优化,在其他设置中无法直接使用。我们展示了gitter,这是一种用于稳健且准确处理基于菌落筛选图像的图像分析工具。gitter的工作原理是首先从预处理图像中找到菌落网格,然后分别定位每个菌落的边界。我们表明,在简单情况下,gitter产生的菌落大小与其他工具相当,但在处理更广泛的筛选类型以及从困难图像中更准确地量化菌落大小时,gitter的表现优于其他工具。gitter作为一个R包可从http://cran.r-project.org/web/packages/gitter免费获取,遵循LGPL许可。教程和演示可在http://omarwagih.github.io/gitter找到。