Multisite assessment of reproducibility in high‐content cell migration imaging data
Abstract High‐content image‐based cell phenotyping provides fundamental insights into a broad variety of life science disciplines. Striving for accurate conclusions and meaningful impact demands high reproducibility standards, with particular relevance for high‐quality open‐access data sharing and m...
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| Format: | Article |
| Language: | English |
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Springer Nature
2023-06-01
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| Series: | Molecular Systems Biology |
| Subjects: | |
| Online Access: | https://doi.org/10.15252/msb.202211490 |
| _version_ | 1797280247776804864 |
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| author | Jianjiang Hu Xavier Serra‐Picamal Gert‐Jan Bakker Marleen Van Troys Sabina Winograd‐Katz Nil Ege Xiaowei Gong Yuliia Didan Inna Grosheva Omer Polansky Karima Bakkali Evelien Van Hamme Merijn vanErp Manon Vullings Felix Weiss Jarama Clucas Anna M Dowbaj Erik Sahai Christophe Ampe Benjamin Geiger Peter Friedl Matteo Bottai Staffan Strömblad |
| author_facet | Jianjiang Hu Xavier Serra‐Picamal Gert‐Jan Bakker Marleen Van Troys Sabina Winograd‐Katz Nil Ege Xiaowei Gong Yuliia Didan Inna Grosheva Omer Polansky Karima Bakkali Evelien Van Hamme Merijn vanErp Manon Vullings Felix Weiss Jarama Clucas Anna M Dowbaj Erik Sahai Christophe Ampe Benjamin Geiger Peter Friedl Matteo Bottai Staffan Strömblad |
| author_sort | Jianjiang Hu |
| collection | DOAJ |
| description | Abstract High‐content image‐based cell phenotyping provides fundamental insights into a broad variety of life science disciplines. Striving for accurate conclusions and meaningful impact demands high reproducibility standards, with particular relevance for high‐quality open‐access data sharing and meta‐analysis. However, the sources and degree of biological and technical variability, and thus the reproducibility and usefulness of meta‐analysis of results from live‐cell microscopy, have not been systematically investigated. Here, using high‐content data describing features of cell migration and morphology, we determine the sources of variability across different scales, including between laboratories, persons, experiments, technical repeats, cells, and time points. Significant technical variability occurred between laboratories and, to lesser extent, between persons, providing low value to direct meta‐analysis on the data from different laboratories. However, batch effect removal markedly improved the possibility to combine image‐based datasets of perturbation experiments. Thus, reproducible quantitative high‐content cell image analysis of perturbation effects and meta‐analysis depend on standardized procedures combined with batch correction. |
| first_indexed | 2024-03-07T16:38:22Z |
| format | Article |
| id | doaj.art-732ee8bfa8294913a63eccb0f9aa6998 |
| institution | Directory Open Access Journal |
| issn | 1744-4292 |
| language | English |
| last_indexed | 2024-03-07T16:38:22Z |
| publishDate | 2023-06-01 |
| publisher | Springer Nature |
| record_format | Article |
| series | Molecular Systems Biology |
| spelling | doaj.art-732ee8bfa8294913a63eccb0f9aa69982024-03-03T09:19:49ZengSpringer NatureMolecular Systems Biology1744-42922023-06-01196n/an/a10.15252/msb.202211490Multisite assessment of reproducibility in high‐content cell migration imaging dataJianjiang Hu0Xavier Serra‐Picamal1Gert‐Jan Bakker2Marleen Van Troys3Sabina Winograd‐Katz4Nil Ege5Xiaowei Gong6Yuliia Didan7Inna Grosheva8Omer Polansky9Karima Bakkali10Evelien Van Hamme11Merijn vanErp12Manon Vullings13Felix Weiss14Jarama Clucas15Anna M Dowbaj16Erik Sahai17Christophe Ampe18Benjamin Geiger19Peter Friedl20Matteo Bottai21Staffan Strömblad22Department of Biosciences and Nutrition Karolinska Institutet Stockholm SwedenDepartment of Biosciences and Nutrition Karolinska Institutet Stockholm SwedenDepartment of Medical BioSciences Radboud University Medical Center Nijmegen The NetherlandsDepartment of Biomolecular Medicine Ghent University Ghent BelgiumDepartment of Immunology and Regenerative Biology Weizmann Institute of Science Rehovot IsraelThe Francis Crick Institute London UKDepartment of Biosciences and Nutrition Karolinska Institutet Stockholm SwedenDepartment of Biosciences and Nutrition Karolinska Institutet Stockholm SwedenDepartment of Immunology and Regenerative Biology Weizmann Institute of Science Rehovot IsraelDepartment of Immunology and Regenerative Biology Weizmann Institute of Science Rehovot IsraelDepartment of Biomolecular Medicine Ghent University Ghent BelgiumBio Imaging Core, VIB Center for Inflammation Research Ghent BelgiumDepartment of Medical BioSciences Radboud University Medical Center Nijmegen The NetherlandsDepartment of Medical BioSciences Radboud University Medical Center Nijmegen The NetherlandsDepartment of Medical BioSciences Radboud University Medical Center Nijmegen The NetherlandsThe Francis Crick Institute London UKThe Francis Crick Institute London UKThe Francis Crick Institute London UKDepartment of Biomolecular Medicine Ghent University Ghent BelgiumDepartment of Immunology and Regenerative Biology Weizmann Institute of Science Rehovot IsraelDepartment of Medical BioSciences Radboud University Medical Center Nijmegen The NetherlandsDivision of Biostatistics, Institute of Environmental Medicine Karolinska Institutet Stockholm SwedenDepartment of Biosciences and Nutrition Karolinska Institutet Stockholm SwedenAbstract High‐content image‐based cell phenotyping provides fundamental insights into a broad variety of life science disciplines. Striving for accurate conclusions and meaningful impact demands high reproducibility standards, with particular relevance for high‐quality open‐access data sharing and meta‐analysis. However, the sources and degree of biological and technical variability, and thus the reproducibility and usefulness of meta‐analysis of results from live‐cell microscopy, have not been systematically investigated. Here, using high‐content data describing features of cell migration and morphology, we determine the sources of variability across different scales, including between laboratories, persons, experiments, technical repeats, cells, and time points. Significant technical variability occurred between laboratories and, to lesser extent, between persons, providing low value to direct meta‐analysis on the data from different laboratories. However, batch effect removal markedly improved the possibility to combine image‐based datasets of perturbation experiments. Thus, reproducible quantitative high‐content cell image analysis of perturbation effects and meta‐analysis depend on standardized procedures combined with batch correction.https://doi.org/10.15252/msb.202211490batch effect removalcell migrationhigh‐content imagingreproducibilityvariability |
| spellingShingle | Jianjiang Hu Xavier Serra‐Picamal Gert‐Jan Bakker Marleen Van Troys Sabina Winograd‐Katz Nil Ege Xiaowei Gong Yuliia Didan Inna Grosheva Omer Polansky Karima Bakkali Evelien Van Hamme Merijn vanErp Manon Vullings Felix Weiss Jarama Clucas Anna M Dowbaj Erik Sahai Christophe Ampe Benjamin Geiger Peter Friedl Matteo Bottai Staffan Strömblad Multisite assessment of reproducibility in high‐content cell migration imaging data Molecular Systems Biology batch effect removal cell migration high‐content imaging reproducibility variability |
| title | Multisite assessment of reproducibility in high‐content cell migration imaging data |
| title_full | Multisite assessment of reproducibility in high‐content cell migration imaging data |
| title_fullStr | Multisite assessment of reproducibility in high‐content cell migration imaging data |
| title_full_unstemmed | Multisite assessment of reproducibility in high‐content cell migration imaging data |
| title_short | Multisite assessment of reproducibility in high‐content cell migration imaging data |
| title_sort | multisite assessment of reproducibility in high content cell migration imaging data |
| topic | batch effect removal cell migration high‐content imaging reproducibility variability |
| url | https://doi.org/10.15252/msb.202211490 |
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