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BactMAP: An R package for integrating, analyzing and visualizing bacterial microscopy data

High‐throughput analyses of single‐cell microscopy data are a critical tool within the field of bacterial cell biology. Several programs have been developed to specifically segment bacterial cells from phase‐contrast images. Together with spot and object detection algorithms, these programs offer po...

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Detalles Bibliográficos
Autores principales: van Raaphorst, Renske, Kjos, Morten, Veening, Jan‐Willem
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7027861/
https://www.ncbi.nlm.nih.gov/pubmed/31693257
http://dx.doi.org/10.1111/mmi.14417
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author van Raaphorst, Renske
Kjos, Morten
Veening, Jan‐Willem
author_facet van Raaphorst, Renske
Kjos, Morten
Veening, Jan‐Willem
author_sort van Raaphorst, Renske
collection PubMed
description High‐throughput analyses of single‐cell microscopy data are a critical tool within the field of bacterial cell biology. Several programs have been developed to specifically segment bacterial cells from phase‐contrast images. Together with spot and object detection algorithms, these programs offer powerful approaches to quantify observations from microscopy data, ranging from cell‐to‐cell genealogy to localization and movement of proteins. Most segmentation programs contain specific post‐processing and plotting options, but these options vary between programs and possibilities to optimize or alter the outputs are often limited. Therefore, we developed BactMAP (Bacterial toolbox for Microscopy Analysis & Plotting), a command‐line based R package that allows researchers to transform cell segmentation and spot detection data generated by different programs into various plots. Furthermore, BactMAP makes it possible to perform custom analyses and change the layout of the output. Because BactMAP works independently of segmentation and detection programs, inputs from different sources can be compared within the same analysis pipeline. BactMAP complies with standard practice in R which enables the use of advanced statistical analysis tools, and its graphic output is compatible with ggplot2, enabling adjustable plot graphics in every operating system. User feedback will be used to create a fully automated Graphical User Interface version of BactMAP in the future. Using BactMAP, we visualize key cell cycle parameters in Bacillus subtilis and Staphylococcus aureus, and demonstrate that the DNA replication forks in Streptococcus pneumoniae dissociate and associate before splitting of the cell, after the Z‐ring is formed at the new quarter positions. BactMAP is available from https://veeninglab.com/bactmap.
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spelling pubmed-70278612020-02-24 BactMAP: An R package for integrating, analyzing and visualizing bacterial microscopy data van Raaphorst, Renske Kjos, Morten Veening, Jan‐Willem Mol Microbiol Research Articles High‐throughput analyses of single‐cell microscopy data are a critical tool within the field of bacterial cell biology. Several programs have been developed to specifically segment bacterial cells from phase‐contrast images. Together with spot and object detection algorithms, these programs offer powerful approaches to quantify observations from microscopy data, ranging from cell‐to‐cell genealogy to localization and movement of proteins. Most segmentation programs contain specific post‐processing and plotting options, but these options vary between programs and possibilities to optimize or alter the outputs are often limited. Therefore, we developed BactMAP (Bacterial toolbox for Microscopy Analysis & Plotting), a command‐line based R package that allows researchers to transform cell segmentation and spot detection data generated by different programs into various plots. Furthermore, BactMAP makes it possible to perform custom analyses and change the layout of the output. Because BactMAP works independently of segmentation and detection programs, inputs from different sources can be compared within the same analysis pipeline. BactMAP complies with standard practice in R which enables the use of advanced statistical analysis tools, and its graphic output is compatible with ggplot2, enabling adjustable plot graphics in every operating system. User feedback will be used to create a fully automated Graphical User Interface version of BactMAP in the future. Using BactMAP, we visualize key cell cycle parameters in Bacillus subtilis and Staphylococcus aureus, and demonstrate that the DNA replication forks in Streptococcus pneumoniae dissociate and associate before splitting of the cell, after the Z‐ring is formed at the new quarter positions. BactMAP is available from https://veeninglab.com/bactmap. John Wiley and Sons Inc. 2019-11-24 2020-01 /pmc/articles/PMC7027861/ /pubmed/31693257 http://dx.doi.org/10.1111/mmi.14417 Text en © 2019 The Authors. Molecular Microbiology published by John Wiley & Sons Ltd This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
van Raaphorst, Renske
Kjos, Morten
Veening, Jan‐Willem
BactMAP: An R package for integrating, analyzing and visualizing bacterial microscopy data
title BactMAP: An R package for integrating, analyzing and visualizing bacterial microscopy data
title_full BactMAP: An R package for integrating, analyzing and visualizing bacterial microscopy data
title_fullStr BactMAP: An R package for integrating, analyzing and visualizing bacterial microscopy data
title_full_unstemmed BactMAP: An R package for integrating, analyzing and visualizing bacterial microscopy data
title_short BactMAP: An R package for integrating, analyzing and visualizing bacterial microscopy data
title_sort bactmap: an r package for integrating, analyzing and visualizing bacterial microscopy data
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7027861/
https://www.ncbi.nlm.nih.gov/pubmed/31693257
http://dx.doi.org/10.1111/mmi.14417
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