Python

CellProfiler is free, open-source software for quantitative analysis of biological images.

CellProfiler is designed to enable biologists without training in computer vision or programming to quantitatively measure cell or whole-organism phenotypes from thousands of images automatically. The researcher creates an analysis pipeline from modules that find cells and cell compartments, measure features of those cells to form a rich, quantitative dataset that characterizes the imaged site in all of its heterogeneity. CellProfiler is structured so that the most general and successful methods and strategies are the ones that are automatically suggested, but the user can override these defaults and pull from many of the basic algorithms and techniques of image analysis to solve harder problems. CellProfiler is extensible through plugins written in Python or for ImageJ. Strengths: Cells, Neurons, C. Elegans, 2D Fluorescent images, high-throughput screening, phenotype classification, multiple stains/site, interoperability, extensibility, machine learning, segmentation Limitations: largely limited to 2D, not well suited to manually-guided analysis or content review, image size limitations

PopulationProfiler – is light-weight cross-platform open-source tool for data analysis in image-based screening experiments. The main idea is to reduce per-cell measurements to per-well distributions, each represented by a histogram. These can be optionally further reduced to sub-type counts based on gating (setting bin ranges) of known control distributions and local adjustments to histogram shape. Such analysis is necessary in a wide variety of applications, e.g. DNA damage assessment using foci intensity distributions, assessment of cell type specific markers, and cell cycle analysis.

BioImageXD is a free open source software package for analyzing, processing and visualizing multi-dimensional microscopy images. It's a collaborative project, designed and developed by microscopists, cell biologists and software engineers from the Universities of Jyväskylä and Turku in Finland, Max Planck Institute CBG in Dresden, Germany and collaborators worldwide. BioImageXD was published in the July 2012 issue of Nature Methods.

MyTardis is free and open-source data management software. It facilitates annotation, sharing and archiving of data and metadata collected from different modalities. It focuses on integration with scientific instruments, instrument facilities and research storage and computing infrastructure; to address the challenges of data storage, data access, collaboration and data publication. It is currently being used to capture data from areas such as optical microscopy, electron microscopy, medical imaging, protein crystallography, neutron and X-ray scattering, flow cytometry, genomics and proteomics.

Key features:

• Easy instrument integration.
• Discipline specific: MX, Imaging, Microscopy, Genomics ...
• Wide range of data formats & supported instruments.
• Secure cloud data storage & access.
• Simple data sharing.
• Researcher controlled data publishing.
• APIs for programmatic access to data and metadata.

A workflow in Python to measure muscule fibers corresponding to the method used in Keefe, A.C. et al. Muscle stem cells contribute to myofibres in sedentary adult mice. Nat. Commun. 6:7087 doi: 10.1038/ncomms8087 (2015).

Example image:

muscleQNT/15536_2032_0.tif ...