OpenComet: An automated tool for comet assay image analysis

Article English OPEN
Benjamin M. Gyori ; Gireedhar Venkatachalam ; P.S. Thiagarajan ; David Hsu ; Marie-Veronique Clement (2014)
  • Publisher: Elsevier
  • Journal: Redox Biology, volume 2, pages 457-465 (issn: 2213-2317, eissn: 2213-2317)
  • Related identifiers: doi: 10.1016/j.redox.2013.12.020, pmc: PMC3949099
  • Subject: Image processing | Intensity profile analysis | Method | Comet assay | R5-920 | DNA damage | Medicine (General) | ImageJ plug-in | Single cell gel electrophoresis | Biology (General) | QH301-705.5

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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