Fly-QMA: Automated analysis of mosaic imaginal discs in Drosophila
Abstract
Mosaic analysis provides a means to probe developmental processes in situ by generating loss-of-function mutants within otherwise wildtype tissues. Combining these techniques with quantitative microscopy enables researchers to rigorously compare RNA or protein expression across the resultant clones. However, visual inspection of mosaic tissues remains common in the literature because quantification demands considerable labor and computational expertise. Practitioners must segment cell membranes or cell nuclei from a tissue and annotate the clones before their data are suitable for analysis. Here, we introduce Fly-QMA, a computational framework that automates each of these tasks for confocal microscopy images of Drosophila imaginal discs. The framework includes an unsupervised annotation algorithm that incorporates spatial context to inform the genetic identity of each cell. We use a combination of real and synthetic validation data to survey the performance of the annotation algorithm across a broad range of conditions. By contributing our framework to the open-source software ecosystem, we aim to contribute to the current move toward automated quantitative analysis among developmental biologists.
Additional Information
© 2020 Bernasek et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Received: September 14, 2019; Accepted: January 27, 2020; Published: March 3, 2020. SMB and LANA were supported by the John and Leslie McQuown Gift. RWC was supported by NIH R35GM118144 (https://www.nih.gov). LANA, NB, and RWC were supported by NSF 1764421 (https://www.nsf.gov). LANA, NB, and RWC were supported by Simons Foundation 597491 (https://www.simonsfoundation.org). NP was supported by the HHMI Hanna H. Gray Fellowship (https://www.hhmi.org/programs/hanna-h-gray-fellows-program). In all cases, the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Data and software availability: We have distributed the automated mosaic analysis framework as an open-source python package available at https://sebastianbernasek.github.io/flyqma. The associated code repository contains resources designed to help users analyze their own microscope images. These include code documentation, a guide to getting started with Fly-QMA, and an interactive tutorial that uses example data to demonstrate the core features of the software. We also intend to incorporate Fly-QMA into future versions of FlyEye Silhouette, our open-source desktop application for quantitative analysis of the larval eye. The code used to generate synthetic microscopy data is also freely available at https://github.com/sebastianbernasek/growth. All segmented and annotated eye discs are accessible via our data repository (https://doi.org/10.21985/N2F207). Author Contributions Conceptualization: Sebastian M. Bernasek, Luı´s A. N. Amaral. Data curation: Sebastian M. Bernasek, Nicola´s Pela´ez. Formal analysis: Sebastian M. Bernasek. Funding acquisition: Richard W. Carthew, Neda Bagheri, Luı´s A. N. Amaral. Investigation: Nicola´s Pela´ez. Methodology: Sebastian M. Bernasek, Nicola´s Pela´ez, Luı´s A. N. Amaral. Project administration: Richard W. Carthew, Neda Bagheri, Luı´s A. N. Amaral. Resources: Richard W. Carthew, Neda Bagheri, Luı´s A. N. Amaral. Software: Sebastian M. Bernasek. Supervision: Richard W. Carthew, Neda Bagheri, Luı´s A. N. Amaral. Validation: Sebastian M. Bernasek. Visualization: Sebastian M. Bernasek. Writing – original draft: Sebastian M. Bernasek. Writing – review & editing: Sebastian M. Bernasek, Nicola´s Pela´ez, Richard W. Carthew, Neda Bagheri, Luı´s A. N. Amaral. The authors have declared that no competing interests exist. Peer Review History: PLOS recognizes the benefits of transparency in the peer review process; therefore, we enable the publication of all of the content of peer review and author responses alongside final, published articles. The editorial history of this article is available here: https://doi.org/10.1371/journal.pcbi.1007406Attached Files
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Additional details
- PMCID
- PMC7100978
- Eprint ID
- 98774
- Resolver ID
- CaltechAUTHORS:20190920-100650519
- John and Leslie McQuown Gift
- R35GM118144
- NIH
- DMS-1764421
- NSF
- 597491
- Simons Foundation
- Howard Hughes Medical Institute (HHMI)
- Created
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2019-09-20Created from EPrint's datestamp field
- Updated
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2023-06-01Created from EPrint's last_modified field