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 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.

CellTracksColab — A platform for compiling, analyzing, and exploring tracking data

“…In addition, CellTracksColab is not currently adapted for lineage tracing studies. Researchers focusing on lineage tracing must explore alternative tools specifically developed for such analyses 1,3,22 .…”

“…Existing image repositories, such as the BioImage Archive 23 and the Image Data Resource 24 , demonstrate the feasibility and value of sharing microscopy data. Analyzed tracking datasets are also very valuable; they hold significant potential for reanalysis and meta-analysis and offer a more manageable alternative to storing raw video footage 25 . Moreover, they can serve the purpose of new machine-learning tracking algorithm development and benchmarking.…”