easyXpress: An R package to analyze and visualize high-throughput C. elegans microscopy data generated using CellProfiler.
| Autor: | Nyaanga J; Department of Molecular Biosciences, Northwestern University, Evanston, IL, United States of America.; Interdisciplinary Biological Sciences Program, Northwestern University, Evanston, IL, United States of America., Crombie TA; Department of Molecular Biosciences, Northwestern University, Evanston, IL, United States of America., Widmayer SJ; Department of Molecular Biosciences, Northwestern University, Evanston, IL, United States of America., Andersen EC; Department of Molecular Biosciences, Northwestern University, Evanston, IL, United States of America. |
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| Jazyk: | angličtina |
| Zdroj: | PloS one [PLoS One] 2021 Aug 12; Vol. 16 (8), pp. e0252000. Date of Electronic Publication: 2021 Aug 12 (Print Publication: 2021). |
| DOI: | 10.1371/journal.pone.0252000 |
| Abstrakt: | High-throughput imaging techniques have become widespread in many fields of biology. These powerful platforms generate large quantities of data that can be difficult to process and visualize efficiently using existing tools. We developed easyXpress to process and review C. elegans high-throughput microscopy data in the R environment. The package provides a logical workflow for the reading, analysis, and visualization of data generated using CellProfiler's WormToolbox. We equipped easyXpress with powerful functions to customize the filtering of noise in data, specifically by identifying and removing objects that deviate from expected animal measurements. This flexibility in data filtering allows users to optimize their analysis pipeline to match their needs. In addition, easyXpress includes tools for generating detailed visualizations, allowing the user to interactively compare summary statistics across wells and plates with ease. Researchers studying C. elegans benefit from this streamlined and extensible package as it is complementary to CellProfiler and leverages the R environment to rapidly process and analyze large high-throughput imaging datasets. Competing Interests: The authors have declared that no competing interests exist. |
| Databáze: | MEDLINE |
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