It’s likely that you didn’t set up the gates in your automated compensation wizard correctly (see more on that here), or you tried to do manual compensation and made a mistake. Being a relatively new CyTOF user, I recently conjugated and titrated almost all my antibodies on helios. The easiest explanation for this situation is that you just didn’t calculate compensation correctly, so you need to go back and fix it. The GatingStrategy class supports the linear, log, channel ratio, inverse hyperbolic sine (asinh), hyperlog, logicle and FlowJo biexponential transformations, as well as Boolean, quadrant, rectangular, elliptical, and polygon gates. So my question: how should I deal with this spillover? Specifically, how do you generate a proper compensation matrix for CyTOF data? I've tried to explain it with some figures (see the PDF in the link below, sorry I didn't figure out how to easily insert pictures into this post) In order to determine the concentration of antibody to use, I have been looking at the separation of signal (low vs high) and the amount of spillover the antibodies generate.Ĭoncerning this last point, I'm not really convinced that compensation is not required for CyTOF. Data were analysed using FlowJo v9 (Tree Star, Inc.) and DIVA softwares (BD Biosciences). Compensation matrices can be read in from multiple sources or created de novo from a set of compensation bead files. I did this to the best of my abilities, but because I'm generating a panel to study mammary tissue, I don't have (m)any ab's that are exclusive.Īll comments and help are much appreciated! I asked around about this and (if people even bother with spillover) they tell me to properly titrate and swap metals around so you don't end up with weak ab's next to strong ab's and also you should know which ab's are mutually exclusive (so you know a certain cell can never have both antibody A and antibody B on it and if you do see it, you gate it out). I prepare my singles similar way as my samples using the same vile of antibody and same staining time, the only difference. I've tried applying compensation matrices to CyTOF data to deal with spillover, but for reasons I don't entirely understand it never seems to work particularly well. I use the CytoFLEX-S machine to run my samples and use FlowJo to analyze. In the case of isotopic impurity in particular, which should be fixed, I would imagine that you should be able to apply a standard matrix based on the known isotopic ratios, but when I've tried to do this the resulting increase in negative noise seems to outweigh any benefits in reducing spillover (much like what you experienced). The compensation matrix is represented by the grid to the left of the sample name. I believe the issue is related to the fact that even if the spillover in channel B may be a fixed percentage of channel A, at lower values of A it falls below the limit of detection in B. Create new, apply old, or compare different matrices. ![]() This means that instead of increasing linearly as signal A goes up, there is a lower/intermediate range of channel A where these is no apparent spillover into channel B and then an uptick once you hit the limit of detection (sort of a "hockey stick").
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