3 – Data analysis

How To Perform A Flow Cytometry t-Test

By: Tim Bushnell, PhD

The ultimate goal of any experiment is to analyze data and determine whether it supports or disproves a given hypothesis. To do that, scientists turn to statistics. If we wish to compare either a single group to a theoretical hypothesis, or two different groups, and these groups are normally distributed, the test of choice is the Student’s t-Test. To perform the t-Test, it is critical to start from the beginning of the experiment to establish several parameters, including the type of test, the null hypothesis, the assumptions about the data, the number of samples to be analyzed (Power of the…

2 Key SPADE Parameters To Adjust For Best Flow Cytometry Results

By: Tim Bushnell, PhD

Mass cytometry panels routinely include 30 or more markers, but traditional analysis methods like bivariate gating can’t adequately parse the resulting high-dimensional data. Spanning-tree progression analysis of density-normalized events (SPADE) is one of the most commonly used computational tools for visualizing and interpreting data sets from mass cytometry and multidimensional fluorescence flow cytometry experiments. There are two key parameters in SPADE that you can adjust in order get the best results possible: downsampling, and target number of nodes or k. Knowing how to properly set these values will enable you to enhance the quality of your analysis.

The Difference Between Linear And Log Displays In Flow Cytometry

By: Tim Bushnell, PhD

We hope this explanation sheds some light on scaling. Knowing how to properly display your data is a critical part of scientific communication. Remember to use linear scaling for most scatter parameters, or when you need to visualize small changes, and log scaling for most fluorescence parameters, or when you need to visualize a wide range of values. As always in flow cytometry, there are certainly exceptions, but armed with this knowledge, you should be able to make educated judgements about which scale types to use in various assays and to better interpret your data.

4 Steps To Validate Flow Cytometry Antibodies And Improve Reproducibility

By: Tim Bushnell, PhD

Until we have access to well-validated recombinant antibodies produced under tightly regulated conditions, researchers need to exercise good judgment regarding these critical biological reagents. These 4 steps will help ensure that your results are consistent and reproducible. This will both reassure your reviewers that your data is of high quality, and allow for researchers at other institutions to successfully replicate your results. In addition, identifying antibody duds early on will save you time and money in the long run. Don’t shirk the work of ensuring your antibodies are working correctly and targeting the right proteins.

Why Understanding Fluorochromes Is Important In Flow Cytometry

By: Tim Bushnell, PhD

Considerations that must be made when choosing fluorochromes include the brightness of the dyes in question, the instrument configuration, and the staining protocol. Each of these factors will impact the quality of the data because of issues related to spectral spillover, staining, loss of signal because of tandem dye degradation, the ability to get an antibody/fluorochrome into a cell, and more. It takes time and effort to develop and optimize a panel. If one fluorochrome doesn’t work, consider why it may have failed and look for alternatives.

5 Steps For Accurate Flow Cytometry Statistical Analysis Results

By: Tim Bushnell, PhD

It is critical to prepare for your statistical analysis at the beginning of the experimental design process. This will ensure the correct data is extracted, the proper test applied, and that sufficient replicates are obtained so that if an effect is to be found, it will be found. Here are five considerations to implement into your experimental design to ensure the best statistical methods so that your data stands up to review.

3 Guidelines For Setting Compensation Controls In Flow Cytometry Experiments

By: Tim Bushnell, PhD

Fluorescence compensation is not possible without proper controls, so it is critical to spend the time and effort to generate high-quality controls in the preparation of an experiment. For a compensation control to be considered “good” or “proper”, each compensation control must be as bright as or brighter than the experimental stain, autofluorescence should be the same for the positive and negative populations used for the compensation calculation in each channel, and the fluorophore used must be the exact fluorophore (i.e. same molecular structure) that is used in the experimental sample.

Strengths And Weaknesses Of Isotype Controls In Flow Cytometry

By: Tim Bushnell, PhD

While controls are critical for minimizing the effects of variables in your flow cytometry experiments, choosing the right controls are essential. When your research is published, reviewers need to see that your variables have been analyzed properly. Evaluating strengths and weaknesses will give you information and back up arguments for the case for or against isotype controls. Here’s a review of what isotype controls are and if you need to use them.

How To Improve Reproducibility Through The Automated Analysis Of Flow Cytometry Data

By: Tim Bushnell, PhD

Flow cytometry (FCM) datasets that are currently being generated will be two orders of magnitude larger than any that exist today. Reproducibility continues to be a critical area that all researchers need to be aware of and researchers need to keep up on best practices to stay relevant. One area that flow cytometry researchers should be focusing on is the emerging changes in the area of automated data analysis. This brief article explains why.

5 Gating Strategies To Get Your Flow Cytometry Data Published In Peer-Reviewed Scientific Journals

By: Tim Bushnell, PhD

When sitting down to perform a new analysis of flow cytometry data, the researcher is guided by very particular laws of nature and a very specific method of working through a biological hypothesis to avoid shaping the results to his or her whims. Following these 5 data analysis and gating strategies through the hierarchy described in this article, researchers are provided with several strategies for identifying and displaying the most relevant data from their flow cytometry experiments.

How To Analyze FACS Data And Prepare Flow Cytometry Figures For Scientific Papers

By: Tim Bushnell, PhD

When preparing figures for publication, the scientific question and hypothesis that forms the basis of the paper must be central and all the figures must be in support of that. The flow cytometry data that forms the basis of the conclusions should be presented clearly and concisely. While it provides pretty pictures and colorful layouts, the meat of the data are the numbers ― percentages of populations, fluorescent intensity levels and the like ― are what will convince the reader that the hypothesis tested is valid and well thought out. Here’s how to choose the correct flow figure for presenting…

4 Critical Components In Cellular Proliferation Measurement

By: Tim Bushnell, PhD

Cellular proliferation is a critical component in biological systems. While normal cell proliferation keeps the body functioning, abnormal proliferation (such as in cancer) can be a target for therapy. There are several critical components in developing, validating and optimizing an assay to make these measures using flow cytometry. Knowing the steps to optimize these assays and properly interpret the results will help ensure the best data and best opportunities are pursued.