彗星
彗星试验
软件
计算机科学
自动化
DNA损伤
计算机视觉
人工智能
计算生物学
生物系统
生物
DNA
工程类
生物化学
机械工程
天体生物学
程序设计语言
作者
Benjamin M. Gyori,Gireedhar Venkatachalam,P. S. Thiagarajan,David Hsu,Marie‐Véronique Clément
出处
期刊:Redox biology
[Elsevier BV]
日期:2014-01-01
卷期号:2: 457-465
被引量:586
标识
DOI:10.1016/j.redox.2013.12.020
摘要
Reactive species such as free radicals are constantly generated in vivo and DNA is the most important target of oxidative stress. Oxidative DNA damage is used as a predictive biomarker to monitor the risk of development of many diseases. The comet assay is widely used for measuring oxidative DNA damage at a single cell level. The analysis of comet assay output images, however, poses considerable challenges. Commercial software is costly and restrictive, while free software generally requires laborious manual tagging of cells. This paper presents OpenComet, an open-source software tool providing automated analysis of comet assay images. It uses a novel and robust method for finding comets based on geometric shape attributes and segmenting the comet heads through image intensity profile analysis. Due to automation, OpenComet is more accurate, less prone to human bias, and faster than manual analysis. A live analysis functionality also allows users to analyze images captured directly from a microscope. We have validated OpenComet on both alkaline and neutral comet assay images as well as sample images from existing software packages. Our results show that OpenComet achieves high accuracy with significantly reduced analysis time.
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