CellProfiler tutorials are exercises we’ve guided groups of users through to help them better understand how to use CellProfiler. Please also check out our examples page, which includes additional pipelines and materials for using CellProfiler with specific samples and imaging applications.
A tutorial showing how to segment cells in CellProfiler and then classify them by phenotype in CellProfiler Analyst. This is our standard tutorial for those new to image analysis in general or CellProfiler in particular.
A tutorial that uses a CellPainting assay to ﬁnd segmentation parameters for larger “parent” objects (nucleus, cell, and cytoplasm) and show you ways to pull out smaller features in your image by segmenting organelles within the nuclei. You will also be shown how to use RelateObjects so that you can relate the average counts, distances, and measurements of the smaller “child” organelles to their larger “parent” objects.
This exercise will guide you through setting segmentation parameters that will be robust across your sample. Additionally, it will show you some ways to pull out smaller features in your image by segmenting organelles within the cells and nuclei. You will learn how to use RelateObjects module to obtain average counts, distances, and measurements of the smaller organelles inside their larger parent objects.
A tutorial that describes building a pipeline to segment the nuclei and cell boundaries of a HeLa cell monolayer in 3d using the Watershed module.
A tutorial describing how to use ilastik in combination with CellProfiler to segment cells imaged only in phase contrast without any added fluorescence.
A tutorial to show how to use CellProfiler plus CellProfiler Analyst to perform quality control on large scale screens.
A tutorial to outlines a method for annotating image data using CellProfiler together with another open source software, GIMP. This method is best for annotating or labeling objects to define their boundaries, exactly, as opposed to annotating an image with bounding boxes or centroids.
A tutorial to introduce you to four modules in CellProfiler; Images, Metadata, NamesAndTypes, and Groups (collectively known as the Input modules). These modules are crucial for any CellProfiler pipeline because they define how images are loaded and organized in CellProfiler for downstream analysis.
A tutorial that describes building a pipeline to segment the nuclei boundaries in noise 3d images using the ReduceNoise and IdentifyPrimaryObjects modules.
A tutorial that describes building a pipeline to segment spots (FISH staining) on C. elegans worms in noise 3d images using background subtraction and Watershed module.
A tutorial that describes how to use the UnmixColors module.
See more video tutorials on the Center for Open Bioimage Analysis (COBA) YouTube account
A tutorial that introduces the concepts behind image-based profiling (aka morphological profiling), which allows you to extract additional and potentially unforseen biological insights from your image data
A blog post on normalizing Cell Painting data for use in image-based profiling.
A tutorial for high-content analysis of imaging flow cytometry (IFC) data with CellProfiler and machine learning can be found here: https://github.com/holgerhennig/machine-learning-IFC
The tutorial is a step by step guide and contains example data, CellProfiler pipelines and a machine learning script (in python) which can serve as a starting point when analyzing your own IFC data.
This tutorial from Carolina Wählby, Maxime Bombrun, and Christian Tischer is a great intro to using CellProfiler to find dots per cell.
Neil Anthony from Emory’s Integrated Cellular Imaging (ICI) core facility has a number of great image analysis tutorials on YouTube, including a 6-part series on CellProfiler.