CellProfiler 4: improvements in speed, utility and usability

David R Stirling,Beth A Cimini,Madison J Swain-Bowden,Alice M Lucas,Allen Goodman,Anne E Carpenter

doi:10.1186/s12859-021-04344-9

Abstract

BackgroundImaging data contains a substantial amount of information which can be difficult to evaluate by eye. With the expansion of high throughput microscopy methodologies producing increasingly large datasets, automated and objective analysis of the resulting images is essential to effectively extract biological information from this data. CellProfiler is a free, open source image analysis program which enables researchers to generate modular pipelines with which to process microscopy images into interpretable measurements.ResultsHerein we describe CellProfiler 4, a new version of this software with expanded functionality. Based on user feedback, we have made several user interface refinements to improve the usability of the software. We introduced new modules to expand the capabilities of the software. We also evaluated performance and made targeted optimizations to reduce the time and cost associated with running common large-scale analysis pipelines.ConclusionsCellProfiler 4 provides significantly improved performance in complex workflows compared to previous versions. This release will ensure that researchers will have continued access to CellProfiler’s powerful computational tools in the coming years.

Highlights

Imaging data contains a substantial amount of information which can be difficult to evaluate by eye
Image analysis software can allow scientists to obtain quantitative measurements from images that are otherwise difficult to capture via subjective observation
In 2005 we introduced CellProfiler, an open-source image analysis program which allows users without specific training to automate their image analysis by using modular processing pipelines [4]

Summary

Introduction

Imaging data contains a substantial amount of information which can be difficult to evaluate by eye. With the expansion of high throughput microscopy methodologies producing increasingly large datasets, automated and objective analysis of the resulting images is essential to effectively extract biological information from this data. Image analysis software can allow scientists to obtain quantitative measurements from images that are otherwise difficult to capture via subjective observation. The increasing use of automated microscopy allows researchers to capture images of samples treated with many thousands of individual compounds or genetic perturbations. Scientists increasingly image cells in 3D or across time series; this expanding bulk of raw data necessitates automated processing and analysis. Such analysis is best achieved through using software to perform automated detection of cells or organisms and extract quantitative metrics which objectively describe the specimens.

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Discussion

Conclusion