Open Source Flow Cytometry Software Mac

  

Flow cytometry (FCM) is a technique used to detect and measure physical and chemical characteristics of a population of cells or particles. In this process, a sample containing cells or particles is suspended in a fluid and injected into the flow cytometer instrument. The sample is focused to ideally flow one cell at a time through a laser beam, where the light scattered is characteristic to. BD FACSDiva™ software provides one of the most complete and robust feature sets available for flow cytometry. BD FACSDiva v9.0 Software BD FACSDiva v9.0 software continues to provide powerful index sorting, along with more routine software operation features including overlays, undo/redo, and multiple copying and pasting of all worksheet elements.

Welcome!

Flow Cytometry Instrumentation. Analysis Software. Analysis Software. Is the data acquisition and analysis program from BD Bioscience and operates in the Macintosh environment on the FACSCalibur cytometers. CellQuest Acquistion Tutorial. CellQuest Analysis Tutorial. Flow cytometry is a technology that simultaneously measures and then analyzes multiple physical characteristics of single particles, usually cells, as they flow in a fluid stream through a beam of light. The properties measured include a particle’s relative size, relative granularity or internal complexity, and relative fluorescence intensity. Version 1.2.1 out now! Greatly improved reading routine should support all possible flow cytometry files! More info 5th Aug, 2008 Due to the bot attack, Idea/Bug discussion is out of order for couple of days. More info Welcome! Cyflogic is a flow cytometry data analysis tool.

Cyflogic is a flow cytometry data analysis tool for Microsoft Windows enviroment. It has all regular analysis capabilities, such as dot plot, histogram and statistics. In addition, Cyflogic offers new innovative tools for your data analysis. Go and check features page to see more!

These pages offer you a newest version of Cyflogic, help, support and discussion about users new ideas, bug fixes, scripts etc.


Current version is 1.2.1

The newest version of Cyflogic is 1.2.1. (released 19th of November, 2008).

If you have older version installed into your computer, go to the Download page and download the latest version! From Version history page you can check the benefits of the new version.

If you want to keep your Cyflogic updated, please visit these pages frequently; new versions appear quite often.


Free version vs. Licenced version

Cyflogic is free for non-commercial academic use. All normal analysis capabilities exist in the free version.

Hovewer, if you buy a licence for your research group / company, you will get the number of extremely nice features, such as cell cycle analysis. Check here for more information.


Philosophy of Cyflogic

Cyflogic offers already some tools which cannot be found anywhere else. But it is not enough for us; we will continue to develop and publish new analysis tools.

Open Source Flow Cytometry Software

Obviously we cannot know exactly what kind of tools you want and whether the existing tools offer you the features you need. That is why this site offers also Development forum, which makes it possible to discuss about new features, ideas and naturally report possible bugs.


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Flow cytometry analysis software free


Author of Cyflogic

Perttu Terho, Mika Korkeamaki, CyFlo Ltd.

CyFlo Ltd, a microbiological and immunological research and development company for the food and feed industry, life sciences sector and other industries interested in microbes and immunity.

Flow cytometry instruments


Disclaimer

©Perttu Terho & ©CyFlo Ltd, Cyflogic analysis software package is for non-commercial research use only and not for use in diagnostic or therapeutic procedures. Not for resale or to be reproduced or copied. Cyflogic software and Cyflogic logo and trademarks are property of CyFlo Ltd. All rights reserved.

Imaging flow cytometry (IFC) combines the high-throughput capabilities of conventional flow cytometry with single-cell imaging. CellProfiler can be used to analyze the resulting images from imaging flow cytometry, whether brightfield, darkfield, or fluorescence.

Flow Cytometry Programs

We here provide an open-source IFC protocol described in Hennig et al. (2016). This protocol aims to enable the scientific community to leverage the full analytical power of IFC-derived data sets. It will help to reveal otherwise unappreciated populations of cells based on features that may be hidden to the human eye. Compensated data files from an imaging flow cytometer (the proprietary .cif file format) can be read and resulting image tiles are generated. The image tiles are imported into the open-source software CellProfiler, where an image processing pipeline identifies cells and subcellular compartments allowing hundreds of morphological features to be measured. This high-dimensional data can then be analyzed using cutting-edge machine learning and clustering approaches using user-friendly platforms such as CellProfiler Analyst or scripting languages such as R or Python.

Note: This is a more user-friendly and streamlined protocol as compared to Blasi et al. (2016), however, the former protocol is still available here.

Papers: H. Hennig, P. Rees, T. Blasi, L. Kamentsky, J. Hung, D. Dao, A.E. Carpenter, and A. Filby. An open-source solution for advanced imaging flow cytometry data analysis using machine learning. Method, in press (2016) [link to paper at Methods]
T. Blasi, H. Hennig, H.D. Summers, F.J. Theis, D. Davies, A. Filby, A.E. Carpenter, P. Rees. Label-free cell cycle analysis for high-throughput imaging flow cytometry. Nat. Comm. 7, 10256 (2016). PMID: 26739115 [link to paper at Nature Communications]

Protocol: [download Protocol_README.txt]

Preparatory Step: Identify cell populations using gating in IDEAS software. Export population as cif file.

Flow Cytometry Instruments

Step 1: Automatically generate tiles of 1000 single cell images per tile, using a python app (alternatively a Matlab script is available). The app reads a cif file and writes the tiles (which are tif image files) to the output folder.

Open Source Flow Cytometry Software Mac Free

[example input cif file] [python app for tiling] [Matlab script for tiling] [example output data]

Step 2: Segment images and extract features in CellProfiler. The example CellProfiler pipeline exports the features as csv files. The pipeline also generates a CellProfiler Analyst properties file for the machine learning in step 3.

[PDF Protocol] [example input data] [CellProfiler pipeline] [example output data]

Step 3: Use any programming language for supervised or unsupervised machine learning, such as python or R. A user-friendly option for machine learning is the softwareCellProfiler Analyst. For this, load the properties file in CellProfilerAnalyst.