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bioRxivBioinformaticsPreprint

Laocoön: a tool for high-throughput automated cell counting

Kaitlin LimiD, Mikaela LouieiD, Anne La Torre, Corinne L. A. Fairchild, Ian F. KorfiD

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Abstract

STRUCTURED ABSTRACTO_ST_ABSMotivationC_ST_ABSThere are current programs and plugins that automatically count the number of cells in a given image. However, many of these processes are not entirely automatic, as they require user input to specify a region of interest and are also frequently inaccurate. ResultsThis project presents laocoon, a Python package specifically designed to automatically and efficiently count the number of fluorescently-labelled cells in images. This package not only allows for reliable cell counting, but returns the proportion of cells in each cell cycle relative to all the cells in the DAPI channel, which is currently used for research purposes, but could ultimately be utilized for clinical purposes. Availability and ImplementationThis package, its corresponding execution instructions, and further information about the underlying algorithms, are currently available in the GitHub repository https://github.com/edukait/laocoon under the MIT license and can be run on the command terminal of any operating system. Alternatively, laocoon is available in the Python Package Index (PyPi), so the user can use the pip command to immediately download the package. Contactkaitlin.y.lim@gmail.com

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