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Understanding Reproducibility in Flow Cytometry – It’s the Antibodies!

Reproducibility in flow cytometry depends on antibody quality
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Reproducibility is key to the scientific method. After the results of a study are published, the community validates the findings and extends them. If the findings are not reproducible, the second step is impossible. With performable experiments increasing in complexity, and the concurrent increase in the cost of equipment and reagents to perform these experiments, it is important to find the best way to maximize the money spent on advancing research. In flow cytometry, there are many places where improvements can be made to increase the consistency and reproducibility of an experiment. The most obvious place is in the instrument, but today’s focus is on the reagents we use to identify cells of interest: Antibodies and fluorochromes.

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3 Components Of Every Flow Cytometer You Don’t Know Enough About

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All flow cytometer instruments have a certain 3 components, and the way they are put together will dictate the performance of the system. As a user, you’ll be interacting heavily with these components, so you need to know both what they are and how they work. There are fluidics, optics, and electronics. The fluidics allow you to interact at the right flow rate so that your data keep a tight CV. Then you can run the same flow rate for all your samples, and you won’t have different CVs for different samples. There are also different optics you can use, like PMTs, APDs, and PDs. It’s important to remember the bandpass filters because they indicate the detector on which your signal will be measured. And with a newer generation of instruments, you can actually change out bandpass filters and design the flow cytometer to your specifications – just make sure you cite the specific bandpass filter that you use. Finally, there are electronics, which process the photon into an electronic signal that is ultimately digitized and stored in a file known as the “FCS file.” An analysis can be performed on this file at a later time.

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4 Steps To Implementing a QC Program For Your Flow Cytometry Experiments

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Quality control is the hallmark of improving reproducibility. QC programs are designed to help determine when the process in question goes off the expected path. Depending on the deviation from the established acceptance criteria will dictate the level of intervention that needs to occur. This can be as easy as cleaning the instrument and rerunning the QC, or as extreme as removing the data from the final analysis. Since there is documentation as to the deviations, this provides the rationale for excluding data.

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5 FlowJo Hacks To Boost The Quality Of Your Flow Cytometry Analysis

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FlowJo is a powerful tool for performing and analyzing flow cytometry experiments, if you know how to use it to the fullest. This includes understanding embedding and using keywords, the FlowJo compensation wizard, spillover spreading matrix, FlowJo and R, and creating tables in FlowJo. Extending your use of FJ using these hacks will help organize your data, improve analysis and make your exported data easier to understand and explain to others. Take a few moments and explore all you can do with FJ beyond just gating populations.

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5 Steps To Improve Your Flow Cytometry Data Analysis

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To get the best flow cytometry data you need to be thinking about all the steps in your experiment to ensure that you have high-quality data to analyze. To improve the quality of your analysis make sure you’re adding keywords at the beginning of your experimental setup, develop a quality control program, trust but verify any software wizards, use proper controls, and make sure you extract the correct data.

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