APA
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Wernersson, E. L. G., Gelali, E., Girelli, G., Wang, S., Castillo, D., Langseth, C., … Bienko, M. (2022). Deconwolf enables high-performance deconvolution of widefield fluorescence microscopy images.
Chicago/Turabian
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Wernersson, Erik L. G., Eleni Gelali, Gabriele Girelli, Su Wang, David Castillo, C. Langseth, Huy Nguyen, et al. “Deconwolf Enables High-Performance Deconvolution of Widefield Fluorescence Microscopy Images” (2022).
MLA
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Wernersson, Erik L. G., et al. Deconwolf Enables High-Performance Deconvolution of Widefield Fluorescence Microscopy Images. 2022.
BibTeX Click to copy
@article{erik2022a,
title = {Deconwolf enables high-performance deconvolution of widefield fluorescence microscopy images},
year = {2022},
author = {Wernersson, Erik L. G. and Gelali, Eleni and Girelli, Gabriele and Wang, Su and Castillo, David and Langseth, C. and Nguyen, Huy and Chattoraj, Shyamtanu and Casals, Anna Martinez and Lundberg, E. and Nilsson, M. and Martí-Renom, M. and Wu, Chao-ting and Crosetto, N. and Bienko, M.}
}
Microscopy-based spatially resolved omic methods are transforming biology and medicine. Currently, these methods rely on high magnification objectives and cannot resolve crowded molecular targets, which limits the amount of biological information that can be extracted from a sample. To overcome these limitations, we developed Deconwolf (DW), an open-source software enabling high-performance deconvolution of widefield fluorescence microscopy image stacks and large tissue scans on a laptop computer. DW significantly outperformed two popular deconvolution tools on images generated by standard immunofluorescence as well as on images of crowded diffraction limited fluorescence dots generated by single-molecule fluorescence in situ hybridization (smFISH) and high-definition DNA FISH. In addition, widefield imaging followed by DW produced images comparable, if not superior in quality to confocal microscopy, but more than 200 times faster. Application of DW to smFISH images enabled accurate quantification of Ki-67 gene transcripts across a tumor microarray tissue core imaged with a 20x air objective. Finally, we applied DW to deconvolve images generated by in situ spatial transcriptomics (ISST) and in situ genomics by OligoFISSEQ. In ISST, DW increased the number of transcripts identified more than three times, while its application to OligoFISSEQ images drastically improved the efficiency of chromosome tracing without the need for signal interpolation. We conclude that DW greatly facilitates the use of deconvolution in many bioimaging applications and paves the way to the application of microscopy-based spatially resolved omic technologies in diagnostics.