cellXpress : a fast and user-friendly software platform for profiling cellular phenotypes
Background: High-throughput, image-based screens of cellular responses to genetic or chemical perturbations generate huge numbers of cell images. Automated analysis is required to quantify and compare the effects of these perturbations. However, few of the current freely-available bioimage analysis...
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sg-ntu-dr.10356-793212022-02-16T16:27:24Z cellXpress : a fast and user-friendly software platform for profiling cellular phenotypes Laksameethanasan, Danai Tan, Rui Zhen Toh, Geraldine Wei-Ling Loo, Lit-Hsin School of Computer Engineering DRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences Background: High-throughput, image-based screens of cellular responses to genetic or chemical perturbations generate huge numbers of cell images. Automated analysis is required to quantify and compare the effects of these perturbations. However, few of the current freely-available bioimage analysis software tools are optimized for efficient handling of these images. Even fewer of them are designed to transform the phenotypic features measured from these images into discriminative profiles that can reveal biologically meaningful associations among the tested perturbations. Results: We present a fast and user-friendly software platform called "cellXpress" to segment cells, measure quantitative features of cellular phenotypes, construct discriminative profiles, and visualize the resulting cell masks and feature values. We have also developed a suite of library functions to load the extracted features for further customizable analysis and visualization under the R computing environment. We systematically compared the processing speed, cell segmentation accuracy, and phenotypic-profile clustering performance of cellXpress to other existing bioimage analysis software packages or algorithms. We found that cellXpress outperforms these existing tools on three different bioimage datasets. We estimate that cellXpress could finish processing a genome-wide gene knockdown image dataset in less than a day on a modern personal desktop computer. Conclusions: The cellXpress platform is designed to make fast and efficient high-throughput phenotypic profiling more accessible to the wider biological research community. ASTAR (Agency for Sci., Tech. and Research, S’pore) Published version 2014-01-10T03:30:50Z 2019-12-06T13:22:30Z 2014-01-10T03:30:50Z 2019-12-06T13:22:30Z 2013 2013 Journal Article Laksameethanasan, D., Tan, R. Z., Toh, G. W.-L., & Loo, L.-H. (2013). cellXpress : a fast and user-friendly software platform for profiling cellular phenotypes. BMC bioinformatics, 14(Suppl 16), S4-. 1471-2105 https://hdl.handle.net/10356/79321 http://hdl.handle.net/10220/18433 10.1186/1471-2105-14-S16-S4 24564609 en BMC bioinformatics © 2013 Laksameethanasan et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution Licens (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. application/pdf |
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DRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences Laksameethanasan, Danai Tan, Rui Zhen Toh, Geraldine Wei-Ling Loo, Lit-Hsin cellXpress : a fast and user-friendly software platform for profiling cellular phenotypes |
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Background: High-throughput, image-based screens of cellular responses to genetic or chemical perturbations generate huge numbers of cell images. Automated analysis is required to quantify and compare the effects of these perturbations. However, few of the current freely-available bioimage analysis software tools are optimized for efficient handling of these images. Even fewer of them are designed to transform the phenotypic features measured from these images into discriminative profiles that can reveal biologically meaningful associations among the tested perturbations. Results: We present a fast and user-friendly software platform called "cellXpress" to segment cells, measure quantitative features of cellular phenotypes, construct discriminative profiles, and visualize the resulting cell masks and feature values. We have also developed a suite of library functions to load the extracted features for further customizable analysis and visualization under the R computing environment. We systematically compared the processing speed, cell segmentation accuracy, and phenotypic-profile clustering performance of cellXpress to other existing bioimage analysis software packages or algorithms. We found that cellXpress outperforms these existing tools on three different bioimage datasets. We estimate that cellXpress could finish processing a genome-wide gene knockdown image dataset in less than a day on a modern personal desktop computer. Conclusions: The cellXpress platform is designed to make fast and efficient high-throughput phenotypic profiling more accessible to the wider biological research community. |
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School of Computer Engineering |
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School of Computer Engineering Laksameethanasan, Danai Tan, Rui Zhen Toh, Geraldine Wei-Ling Loo, Lit-Hsin |
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Article |
author |
Laksameethanasan, Danai Tan, Rui Zhen Toh, Geraldine Wei-Ling Loo, Lit-Hsin |
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Laksameethanasan, Danai |
title |
cellXpress : a fast and user-friendly software platform for profiling cellular phenotypes |
title_short |
cellXpress : a fast and user-friendly software platform for profiling cellular phenotypes |
title_full |
cellXpress : a fast and user-friendly software platform for profiling cellular phenotypes |
title_fullStr |
cellXpress : a fast and user-friendly software platform for profiling cellular phenotypes |
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cellXpress : a fast and user-friendly software platform for profiling cellular phenotypes |
title_sort |
cellxpress : a fast and user-friendly software platform for profiling cellular phenotypes |
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2014 |
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https://hdl.handle.net/10356/79321 http://hdl.handle.net/10220/18433 |
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1725985503327551488 |