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Cellprofiler cell intensity1/8/2023 For that purpose, a Galaxy tool was developed in collaboration with EOSC-Life WP1, that directly connects to the IDR, with advanced error handling, and makes bulk-downloads possible.Īn exemplary workflow has been created using these tools as part of Demonstrator 6 of EOSC-Life WP3. The outcome will vary depending on the design of the workflow: segmentation masks for each object identified, features associated with images or any of the objects segmented, images with metadata overlaid on top of the identified objects, among others.Īnother approach is to reuse public data from previous studies that are available at the Image Data Resource (IDR). Scientists can now upload their own images to a Galaxy instance and build workflows combining these tools to address different biological questions. For complete images -or mathematical combinations of them-, features like the quality, the intensity, and the area occupied by objects can also be easily extracted. At the level of the objects identified, several parameters can be measured (granularity, texture, intensity, size, shape, etc.), along with the relationships between objects. Several segmentation methods can be applied (Manual, Measurement, Minimum cross entropy, Otsu and Robust background) to all image types supported by CellProfiler. Blue dot represents median integrated intensity values of cells cultured on the flat surface.In total, 22 modules have been integrated into 19 Galaxy tools, providing scientists with a comprehensive suite to perform the most prevailing functionalities: object segmentation and feature extraction. Black dots represent median integrated intensities of individual TopoUnits. C) Extraction of integrated intensity measurements of protein of interest reveals a steady upregulation when cells are cultured on micro-topographies. A) Segmentation of nuclear and cellular morphology B) ICC against the protein of interest located in the nucleus. Quantitative image analysis of protein of interest. Further data analysis through machine-learning algorithms can reveal the association between morphological features and the upregulation of the protein of interest. Subsequent data-analysis is performed in R and reveals a steady upregulation of the protein of interest when cells are cultured on micro-topographies. Here, we analyzed 29435 cells to extract cellular and nuclear morphological features and protein intensity levels through ICC. Top left: original image (U2OS cells on NanoTopoChip), top right: identified single fibers bottom left: identified cell body and nuclei bottom right: morphological features extracted from the shape of the fibers.Īnother example is the quantification of a protein of interest of cells cultured on multiple TopoChips. Examples here include the segmentation of actin fibers, providing us with data concerning the orientation, localization and the number of fibers in different experimental settings.Įxtracting morphological features of actin fibers. CellProfiler enables us to design custom-made modules that allow us to extract both quantitative and qualitative features from our acquired images. For this, we routinely utilize CellProfiler, a program designed by the Broad Institute of Harvard and MIT. Research at the cBITE group is characterized by both high-content and high-throughput image analysis. High throughput image screening using CellProfiler
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