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. 2021 Jul 28;11:15319. doi: 10.1038/s41598-021-94850-w

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© The Author(s) 2021, corrected publication 2021

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Speck image analysis pipeline. (a) All nuclei (blue) were segmented, and the total number of nuclei were counted. (b) Very bright mCherry fluorescent cells were removed from the analysis to avoid incorrect speck segmentation. This was achieved by measuring the mCherry intensity in the nucleus minus spot masks (see inset) and rejecting cells above a fixed intensity level threshold (red) and selected nuclei (blue) were retained. (c) Nuclei were dilated (yellow) to give a pseudo cell region where specks were counted. (d) Specks were segmented. (e) The selected nuclei, dilated nuclei and specks were linked together to yield the total number of cells with specks. (f) The final calculation consisted of the ratio between the total number of cells with specks and the total number of nuclei and multiplying it to 100 to calculate the percentage of cells with specks. (g) Example segmentation overlay after analysis, nuclei (blue), cells (yellow) and specks (red).