Journal article
Mahmoud Ahmed, Trang Huyen Lai, Deok Ryong Kim
PeerJ, vol. 7, 2019 Jun 4
PeerJ, vol. 7, 2019 Jun 4
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APA
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Ahmed, M., Lai, T. H., & Kim, D. R. (2019). colocr: an R package for conducting co-localization analysis on fluorescence microscopy images. PeerJ, 7.
Chicago/Turabian
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Ahmed, Mahmoud, Trang Huyen Lai, and Deok Ryong Kim. “Colocr: an R Package for Conducting Co-Localization Analysis on Fluorescence Microscopy Images.” PeerJ 7 (June 4, 2019).
MLA
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Ahmed, Mahmoud, et al. “Colocr: an R Package for Conducting Co-Localization Analysis on Fluorescence Microscopy Images.” PeerJ, vol. 7, June 2019.
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@article{mahmoud2019a,
title = {colocr: an R package for conducting co-localization analysis on fluorescence microscopy images.},
year = {2019},
month = jun,
day = {4},
journal = {PeerJ},
volume = {7},
author = {Ahmed, Mahmoud and Lai, Trang Huyen and Kim, Deok Ryong},
month_numeric = {6}
}
Abstract
Background: The co-localization analysis of fluorescence microscopy images is a widely used technique in biological research. It is often used to determine the co-distribution of two proteins inside the cell, suggesting that these two proteins could be functionally or physically associated. The limiting step in conducting microscopy image analysis in a graphical interface tool is the selection of the regions of interest for the co-localization of two proteins.
Implementation: This package provides a simple straightforward workflow for loading fluorescence images, choosing regions of interest and calculating co-localization measurements. Included in the package is a shiny app that can be invoked locally to interactively select the regions of interest where two proteins are co-localized.
Availability: colocr is available on the comprehensive R archive network, and the source code is available on GitHub under the GPL-3 license as part of the ROpenSci collection, https://github.com/ropensci/colocr.
Implementation: This package provides a simple straightforward workflow for loading fluorescence images, choosing regions of interest and calculating co-localization measurements. Included in the package is a shiny app that can be invoked locally to interactively select the regions of interest where two proteins are co-localized.
Availability: colocr is available on the comprehensive R archive network, and the source code is available on GitHub under the GPL-3 license as part of the ROpenSci collection, https://github.com/ropensci/colocr.