MyoCount: a software tool for the automated quantification of myotube surface area and nuclear fusion index
dc.contributor.author | Murphy, DP | |
dc.contributor.author | Nicholson, T | |
dc.contributor.author | Jones, SW | |
dc.contributor.author | O'Leary, MF | |
dc.date.accessioned | 2019-03-14T14:04:07Z | |
dc.date.issued | 2019-03-13 | |
dc.description.abstract | It is often desirable to characterise the morphology of myogenic cultures. To achieve this, the surface area of myotubes is often quantified, along with the nuclear fusion index (NFI). Existing methods of such quantification are time-consuming and subject to error-prone human input. We have developed MyoCount, an open-source program that runs via the freely available MATLAB Runtime and quantifies myotube surface area and NFI. MyoCount allows the user to adjust its parameters to account for differences in image quality, magnification and the colour channels used in generating the image. MyoCount measures of myotube surface area and NFI were compared to the mean of measures performed by two blinded investigators using ImageJ software (surface area R2 = 0.89, NFI R2 =0.87). For NFI, the mean coefficient of variation (CV) between two investigators (17.6 ± 2.3%) was significantly higher than that between the investigator mean and MyoCount (13.5 ± 1.4%). For measurements of myotube area, the CV did not differ between both analysis methods. Given these results and the advantages of applying the same image analysis method uniformly across all images in an experiment, we suggest that MyoCount will be a useful research tool and we publish its source code and instructions for its use alongside this article. | en_GB |
dc.description.sponsorship | Wellcome Trust | en_GB |
dc.identifier.citation | Vol. 4, article 6 | en_GB |
dc.identifier.doi | 10.12688/wellcomeopenres.15055.1 | |
dc.identifier.grantnumber | 102284 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/36465 | |
dc.language.iso | en | en_GB |
dc.publisher | F1000Research | en_GB |
dc.rights | © 2019 Murphy DP et al. This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. | en_GB |
dc.subject | Image analysis | en_GB |
dc.subject | skeletal muscle | en_GB |
dc.subject | myotube | en_GB |
dc.subject | cell culture | en_GB |
dc.title | MyoCount: a software tool for the automated quantification of myotube surface area and nuclear fusion index | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2019-03-14T14:04:07Z | |
dc.identifier.issn | 2398-502X | |
dc.description | This is the author accepted manuscript. The final version is available on open access from F1000Research via the DOI in this record | en_GB |
dc.description | Data availability: The data underlying the results presented in Figure 4 and Figure 5, (.csv and .tif files) are available as ‘Myocount Validation Data’ via OSF. DOI: https://doi.org/10.17605/OSF.IO/F5DXE18. Data are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication). Software availability: Latest source code and Myocount version are available at: https://github.com/MurphyDavid/MyoCount/releases. Archived source code at time of publication: https://doi.org/10.5281/zenodo.254281111. License: MIT License. https://opensource.org/licenses/MIT | en_GB |
dc.identifier.journal | Wellcome Open Research | en_GB |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2019-03-13 | |
rioxxterms.version | AM | en_GB |
rioxxterms.licenseref.startdate | 2019-03-13 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2019-03-14T11:48:01Z | |
refterms.versionFCD | AM | |
refterms.dateFOA | 2019-03-14T14:04:15Z | |
refterms.panel | C | en_GB |
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Except where otherwise noted, this item's licence is described as © 2019 Murphy DP et al. This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.