Abstract
Study of cell populations in tissues using immunofluorescence is a powerful method for both basic and medical research. Image acquisitions performed by confocal microscopy notably allow excellent lateral resolution and more than 10 parameter measurement when using spectral or multiplex imaging. Analysis of such complex images can be very challenging and easily lead to bias and misinterpretation. Here, we have developed the Shiny Analytical Plot of Histological Image Results (SAPHIR), an R shiny application for histo-cytometry using scatterplot representation of data extracted by segmentation. It offers many features, such as filtering of spurious data points, selection of cell subsets on scatterplot, visualization of scatterplot selections back into the image, statistics of selected data and data annotation. Our application allows to quickly characterize labeled cells, from their phenotype to their number and location in the tissue, as well as their interaction with other cells. SAPHIR is available from: https://github.com/elodiegermani/SAPHIR.
Highlights
The identification, localization and quantification of cell subsets in tissue is a difficult but essential task for biologists to understand spatial cellular organization in different settings
Like flow cytometry, complex image analysis can benefit from scatterplot representations that allow to gate cells of interest[2,8]
In existing software, this scatterplot representation is rarely interactive with the image itself, this would allow to locate selection results back into the image and to filter or correct results and fine-tune the gates defining cell populations to obtain in return a better visualization of them into the image
Summary
1. Mahmoud Ahmed , Gyeongsang National University School of Medicine, Jinju, South Korea Trang Huyen Lai , Gyeongsang National University School of Medicine, Jinju, South Korea. This article is included in the NEUBIAS - the Bioimage Analysts Network gateway. Any reports and responses or comments on the article can be found at the end of the article
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