TheCellVision.org: A Database for Visualizing and Mining High-Content Cell Imaging Projects
Myra Paz David Masinas*,1, Mojca Mattiazzi Usaj*,1,2, Matej Usaj*, Charles Boone*,#,2, and Brenda J. Andrews*,#,2
- *The Donnelly Centre, University of Toronto, Toronto, Ontario, M5S 3E1, Canada
- #Department of Molecular Genetics, University of Toronto, Toronto, Ontario, M5S 3E1, Canada
- 1These authors contributed equally to this work
- 2Corresponding authors
Abstract
Advances in genome engineering and high throughput imaging technologies have enabled genome- scale screens of single cells for a variety of phenotypes, including subcellular morphology and protein localization. We constructed TheCellVision.org, a freely available and web-accessible image visualization and data browsing tool that serves as a central repository for fluorescence microscopy images and associated quantitative data produced by high-content screening experiments. Currently, TheCellVision.org hosts ~575,590 images and associated analysis results from two published high- content screening (HCS) projects focused on the budding yeast Saccharomyces cerevisiae TheCellVision.org allows users to access, visualize and explore fluorescence microscopy images, and to search, compare, and extract data related to subcellular compartment morphology, protein abundance, and localization. Each dataset can be queried independently or as part of a search across multiple datasets using the advanced search option. The website also hosts computational tools associated with the available datasets, which can be applied to other projects and cell systems, a feature we demonstrate using published images of mammalian cells. Providing access to HCS data through websites such as TheCellVision.org enables new discovery and independent re-analyses of imaging data.
Expanding TheCellVision.org: A Central Repository for Visualizing and Mining High-Content Cell Imaging Projects
Myra Paz David Masinas1,*, Athanasios Litsios1,*, Anastasia Razdaibiedina 1,2,3, Matej Usaj1, Charles Boone1,2,#, and Brenda J. Andrews1,2,#
- 1The Donnelly Centre, University of Toronto, Toronto, Ontario, M5S 3E1, Canada
- 2Department of Molecular Genetics, University of Toronto, Toronto, Ontario, M5S 3E1, Canada
- 3Vector Institute for Artificial Intelligence, Toronto, Ontario, M5G 1N1, Canada
- *These authors contributed equally to this work
- #Corresponding authors
Abstract
We previously constructed TheCellVision.org, a central repository for visualizing and mining data from yeast high-content imaging projects. At its inception, TheCellVision.org housed two high-content screening (HCS) projects providing genome-scale protein abundance and localization information for the budding yeast Saccharomyces cerevisiae, as well as a comprehensive analysis of the morphology of its endocytic compartments upon systematic genetic perturbation of each yeast gene. Here, we report on the expansion of TheCellVision.org by the addition of two new HCS projects and the incorporation of new global functionalities. Specifically, TheCellVision.org now hosts images from the Cell Cycle Omics project, which describes genome-scale cell cycle-resolved dynamics in protein localization, protein concentration, gene expression, and translational efficiency in budding yeast. Moreover, it hosts PIFiA, a computational tool for image-based predictions of protein functional annotations. Across all its projects, TheCellVision.org now houses > 800,000 microscopy images along with computational tools for exploring both the images and their associated datasets. Together with the newly added global functionalities, which include the ability to query genes in any of the hosted projects using either yeast or human gene names, TheCellVision.org provides an expanding resource for single-cell eukaryotic biology.
Contact Us
- Brenda Andrews
- Myra Paz David Masinas (website technical questions)
External Database Resources
- The list of Saccharomyces cerevisiae genes used on this website were retrieved from the SGD Project; URL: http://sgd-archive.yeastgenome.org/curation/chromosomal_feature/SGD_features.tab [Date file retrieval: 2019-02-26]
- The list of human orthologs used on this website were retrieved from the Alliance of Genome Resources; URL: https://www.alliancegenome.org [Date file retrieval: 2024-02-27; Alliance Database Version: 7.0.0]
Thanks to the following libraries and their developers
