Cytometry techniques are widely used to analyze cellular characteristics at single-cell resolution. This allows forstudying disease-specific mechanisms and potential drug targets, as well as pre-clinical therapy response indiseases such as atherosclerosis and breast cancer [1], [2].Many data analysis methods for cytometry data focus solely on identifying subpopulations via clustering andtesting for differential cell abundance. However, besides abundance, it can be important to observe if specificmarker genes differ between sample groups. This is relevant for detecting if potential drug targets are uniformlyexpressed across a cell population [3]. Only few tools offer differential expression analysis of markers betweenconditions. These either reduce the data distribution to medians, discarding valuable information, or haveunderlying assumptions that may not hold for all expression patterns.We systematically evaluated existing and novel approaches for differential expression analysis on real andsimulated CyTOF data and found that methods using median marker expressions compute fast and reliableresults when the data are not strongly zero-inflated. However, as zero inflation of drug response genes isexpected after drug exposure, methods using all data to robustly detect changes in zero-inflated markers areneeded. To account for this, we developed the method CyEMD which uses earth mover’s distance to compareexpression distributions and can handle strong zero-inflation. CyEMD is available through CYANUS - CYtometryANalysis Using Shiny - a user-friendly R Shiny App, allowing the user to analyze cytometry data withstate-of-the-art tools, including well-performing methods from our comparison. A public web interface is availableat https://exbio.wzw.tum.de/cyanus/ [4].
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Georgopoulou Dimitra, Callari Maurizio, Rueda Oscar M., Shea Abigail, Martin Alistair, Giovannetti Agnese, Qosaj Fatime, Dariush Ali, Chin Suet-Feung, Carnevalli Larissa S., Provenzano Elena, Greenwood Wendy, Lerda Giulia, Esmaeilishirazifard Elham, O’Reilly Martin, Serra Violeta, Bressan Dario, Mills Gordon B., Ali H. Raza, Cosulich Sabina S., Hannon Gregory J., Bruna Alejandra, Caldas Carlos. Landscapes of cellular phenotypic diversity in breast cancer xenografts and their impact on drug response. Nature Communications. Vol. 12(1)2021. Springer Science and Business Media LLC. [Cross Ref]
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Arend Lis, Bernett Judith, Manz Quirin, Klug Melissa, Lazareva Olga, Baumbach Jan, Bongiovanni Dario, List Markus. A systematic comparison of novel and existing differential analysis methods for CyTOF data. Briefings in Bioinformatics. Vol. 23(1)2022. Oxford University Press (OUP). [Cross Ref]