For each sample, you can perform various actions like adding keywords or statistics, display data sets in a spatial spinnable visualization window and concatenate files together. By right-clicking a sample, you can modify group settings, including name, color, font style, role, sample inclusion criterion and assignments. The Group section allows you to organize samples in the order in which you want to analyze them. Moreover, you can drag and drop samples or bands on the workspace. The application provides you with the means to customize each band with the preferred tasks that you commonly use. The interface of FlowJo is user-friendly and consists of the main workspace and several ribbons that contain tabbed bands which allow you to scroll through various bands to access different tasks. Performing a flow cytometry analysis is crucial to diagnose health disorders, especially blood cancers, but it can be helpful to other specialized applications for research and clinical practice purposes.Д¬ustomizable and easy to navigate interface Importantly, the affect scaling can have on actually visualizing the median value of a population.Treestar FlowJo 10.5.3 (ењ†4) | File Size: 157 MBДЇlowJo is a powerful application that provides you with an integrated environment for displaying and analyzing flow cytometric data. ДЄn amazing article explaining when and why to use bi-exponential axes. Ultimately, like any piece of data, MFI should only be applied if you are absolutely certain that it is the best comparison to make, otherwise it is simply clutter on an otherwise clean histogram.ДЇlowjoвЂ™s excellent explanation of the differences between mean, median and mode. MFI has many important uses, but can sometimes be as much a distraction from the data as it is a clarification. Thus, it is important to control carefully for things such as size or compensation that may confound results. For example, a large cell with more membrane and consequently more surface protein, can appear brighter than a smaller cell of the same type. Additionally, it is tempting to say that a population with a higher MFI has higher expression than one with a lower MFI, however, care must be taken to ensure other factors are not responsible. antibody dilution, tandem dye degradation, laser fluctuations, etc.), it is dangerous to compare intensity of any kind across multiple experiments.Д«lindly using MFI as a quantification of expression: While FACS is more than sensitive enough to provide estimates of ligand abundance, such calculations require normalization and calibration using a standard curve. Statistics aside, gating each population and presenting percentages will yield data that is both more easily interpretable as well as more statistically significant.Д¬omparing data from disparate experiments: Because fluorescent intensity is sensitive to experimental condition (e.g. But generally speaking, median is the safest choice and usually most representative of a вЂњtypicalвЂќ cell.Д¬haracterizing a bi-modal population: Any average only holds true for normal distributions, and a bi-modal population is by definition not normal. Is there a вЂњrightвЂќ MFI to use to analyze flow data? No. Median is considered a much more robust statistic in that it is less influenced by skew or outliers. This leaves us with the median or the mid-point of the population. To combat this, geometric mean (gMFI) is often used to account for the log-normal behavior of flow data, however, even gMFI is susceptible to significant shifts. The more that the data skews, the further the mean drifts in the direction of skew and becomes less representative of the data being analyze as seen on the graphical representation.Д«ecause fluorescent intensity increases logarithmically, arithmetic mean quickly becomes useless to generalize a population of events, as a right-hand skew causes even more exaggeration of the mean. In reality, flow data is rarely normal and never perfect. In a perfect world, our data would be normally distributed and in that case means, median and mode are all equal. MFI is often used without explanation, to abbreviate either arithmetic mean, geometric mean, or median fluorescence intensity. The first point of confusion is born from the name itself. One of the more commonly misunderstood and often misleading tools in FACS analysis is a pesky little statistic - MFI. The fact is that with potentially millions of data points accrued over the run of a single sample, finding the best way to compare those data can be daunting. The speed, sensitivity and versatility of flow cytometry are things of beauty, but with great power comes great responsibility. Understanding MFI in the context of FACS data

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