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      CYANUS - a web platform for analyzing drug response markers in cytometry data

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      proceedings-article
        1 ,   1 ,   1 , , 1 , 1 ,   2 , 3 , 1
      ScienceOpen
      RExPO22
      2-3 September, 2022
      cytometry, CyTOF, differential expression analysis, benchmark, drug response
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            Abstract

            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].

            Content

            Author and article information

            Conference
            ScienceOpen
            26 August 2022
            Affiliations
            [1 ] Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Munich, Germany
            [2 ] Chair of Computational Systems Biology, University of Hamburg, Hamburg, Germany
            [3 ] Department of Internal Medicine I, School of Medicine, University Hospital rechts der Isar, Technical University of Munich, Munich, Germany
            Author notes
            Author information
            https://orcid.org/0000-0001-7990-8385
            https://orcid.org/0000-0001-5812-8013
            https://orcid.org/0000-0002-5706-2718
            https://orcid.org/0000-0001-5193-2770
            https://orcid.org/0000-0001-9546-7807
            https://orcid.org/0000-0002-0282-0462
            https://orcid.org/0000-0002-4162-1482
            https://orcid.org/0000-0002-0941-4168
            Article
            10.14293/S2199-1006.1.SOR-.PPP5QEXA.v1
            72f48977-cba5-4687-995b-4111ad9e7096

            This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .

            RExPO22
            Maastricht, Netherlands
            2-3 September, 2022
            History
            : 26 August 2022

            The datasets generated during and/or analysed during the current study are available in the repository: https://flowrepository.org/id/FR-FCM-Z4AE, https://exbio.wzw.tum.de/cyanus/
            drug response,differential expression analysis,CyTOF,cytometry,benchmark

            References

            1. Fernandez Dawn M., Giannarelli Chiara. Immune cell profiling in atherosclerosis: role in research and precision medicine. Nature Reviews Cardiology. Vol. 19(1):43–58. 2022. Springer Science and Business Media LLC. [Cross Ref]

            2. 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]

            3. Bongiovanni Dario, Klug Melissa, Lazareva Olga, Weidlich Simon, Biasi Marina, Ursu Simona, Warth Sarah, Buske Christian, Lukas Marina, Spinner Christoph D., Scheidt Moritz von, Condorelli Gianluigi, Baumbach Jan, Laugwitz Karl-Ludwig, List Markus, Bernlochner Isabell. SARS-CoV-2 infection is associated with a pro-thrombotic platelet phenotype. Cell Death & Disease. Vol. 12(1)2021. Springer Science and Business Media LLC. [Cross Ref]

            4. 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]

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