Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/79321
Title: | cellXpress : a fast and user-friendly software platform for profiling cellular phenotypes | Authors: | Laksameethanasan, Danai Tan, Rui Zhen Toh, Geraldine Wei-Ling Loo, Lit-Hsin |
Keywords: | DRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences | Issue Date: | 2013 | Source: | 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-. | Series/Report no.: | BMC bioinformatics | Abstract: | 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. | URI: | https://hdl.handle.net/10356/79321 http://hdl.handle.net/10220/18433 |
ISSN: | 1471-2105 | DOI: | 10.1186/1471-2105-14-S16-S4 | Schools: | School of Computer Engineering | Rights: | © 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. | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | SCSE Journal Articles |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
cellXpress a fast and user-friendly software platform for profiling cellular phenotypes.pdf | 2.94 MB | Adobe PDF | View/Open |
SCOPUSTM
Citations
20
21
Updated on Mar 25, 2024
Web of ScienceTM
Citations
20
22
Updated on Oct 26, 2023
Page view(s) 50
470
Updated on Mar 28, 2024
Download(s) 20
269
Updated on Mar 28, 2024
Google ScholarTM
Check
Altmetric
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.