Multisite assessment of reproducibility in high‐content cell migration imaging data
- Author
- Jianjiang Hu, Xavier Serra‐Picamal, Gert‐Jan Bakker, Marleen Van Troys (UGent) , Sabina Winograd‐Katz, Nil Ege, Xiaowei Gong, Yuliia Didan, Inna Grosheva, Omer Polansky, Karima Bakkali (UGent) , Evelien Van Hamme (UGent) , Merijn van Erp, Manon Vullings, Felix Weiss, Jarama Clucas, Anna M Dowbaj, Erik Sahai, Christophe Ampe (UGent) , Benjamin Geiger, Peter Friedl, Matteo Bottai and Staffan Strömblad
- Organization
- Project
-
- MULTIMOT (Capture, dissemination and analysis of multiscale cell migration data for biological and clinical applications (MULTIMOT))
- MEMCLIP: A comprehensive chemical-biology approach to understand the bioactivity of Pseudomonas cyclic lipopeptides on eukaryotic membranes
- 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.
- Keywords
- Applied Mathematics, Computational Theory and Mathematics, General Agricultural and Biological Sciences, General Immunology and Microbiology, General Biochemistry, Genetics and Molecular Biology, Information Systems, batch effect removal, cell migration, high-content imaging, reproducibility, variability
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01GZECR8QWJ7F2D6B6QXJ670HX
- MLA
- Hu, Jianjiang, et al. “Multisite Assessment of Reproducibility in High‐content Cell Migration Imaging Data.” MOLECULAR SYSTEMS BIOLOGY, vol. 19, no. 6, 2023, doi:10.15252/msb.202211490.
- APA
- Hu, J., Serra‐Picamal, X., Bakker, G., Van Troys, M., Winograd‐Katz, S., Ege, N., … Strömblad, S. (2023). Multisite assessment of reproducibility in high‐content cell migration imaging data. MOLECULAR SYSTEMS BIOLOGY, 19(6). https://doi.org/10.15252/msb.202211490
- Chicago author-date
- Hu, Jianjiang, Xavier Serra‐Picamal, Gert‐Jan Bakker, Marleen Van Troys, Sabina Winograd‐Katz, Nil Ege, Xiaowei Gong, et al. 2023. “Multisite Assessment of Reproducibility in High‐content Cell Migration Imaging Data.” MOLECULAR SYSTEMS BIOLOGY 19 (6). https://doi.org/10.15252/msb.202211490.
- Chicago author-date (all authors)
- Hu, Jianjiang, 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 van Erp, Manon Vullings, Felix Weiss, Jarama Clucas, Anna M Dowbaj, Erik Sahai, Christophe Ampe, Benjamin Geiger, Peter Friedl, Matteo Bottai, and Staffan Strömblad. 2023. “Multisite Assessment of Reproducibility in High‐content Cell Migration Imaging Data.” MOLECULAR SYSTEMS BIOLOGY 19 (6). doi:10.15252/msb.202211490.
- Vancouver
- 1.Hu J, Serra‐Picamal X, Bakker G, Van Troys M, Winograd‐Katz S, Ege N, et al. Multisite assessment of reproducibility in high‐content cell migration imaging data. MOLECULAR SYSTEMS BIOLOGY. 2023;19(6).
- IEEE
- [1]J. Hu et al., “Multisite assessment of reproducibility in high‐content cell migration imaging data,” MOLECULAR SYSTEMS BIOLOGY, vol. 19, no. 6, 2023.
@article{01GZECR8QWJ7F2D6B6QXJ670HX,
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.}},
articleno = {{e11490}},
author = {{Hu, Jianjiang and Serra‐Picamal, Xavier and Bakker, Gert‐Jan and Van Troys, Marleen and Winograd‐Katz, Sabina and Ege, Nil and Gong, Xiaowei and Didan, Yuliia and Grosheva, Inna and Polansky, Omer and Bakkali, Karima and Van Hamme, Evelien and van Erp, Merijn and Vullings, Manon and Weiss, Felix and Clucas, Jarama and Dowbaj, Anna M and Sahai, Erik and Ampe, Christophe and Geiger, Benjamin and Friedl, Peter and Bottai, Matteo and Strömblad, Staffan}},
issn = {{1744-4292}},
journal = {{MOLECULAR SYSTEMS BIOLOGY}},
keywords = {{Applied Mathematics,Computational Theory and Mathematics,General Agricultural and Biological Sciences,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,Information Systems,batch effect removal,cell migration,high-content imaging,reproducibility,variability}},
language = {{eng}},
number = {{6}},
pages = {{15}},
title = {{Multisite assessment of reproducibility in high‐content cell migration imaging data}},
url = {{http://doi.org/10.15252/msb.202211490}},
volume = {{19}},
year = {{2023}},
}
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