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{"title":"获得高质量的流式细胞术数据。","authors":"Amy Fox, Taru S Dutt, Burton Karger, Andrés Obregón-Henao, G Brooke Anderson, Marcela Henao-Tamayo","doi":"10.1002/cpcy.74","DOIUrl":null,"url":null,"abstract":"<p><p>Flow cytometry allows the visualization of physical, functional, and/or biological properties of cells including antigens, cytokines, size, and complexity. With increasingly large flow cytometry panels able to analyze up to 50 parameters, there is a need to standardize flow cytometry protocols to achieve high-quality data that can be input into analysis algorithms. Without this clean data, algorithms may incorrectly categorize the cell populations present in the samples. In this protocol, we outline a comprehensive methodology to prepare samples for polychromatic flow cytometry. The use of multiple washing steps and rigorous controls creates high-quality data with good separation between cell populations. Experimental data acquired using this protocol can be analyzed via computational algorithms that perform end-to-end analysis. © 2020 by John Wiley & Sons, Inc. Basic Protocol 1: Preparation of single-cell suspension for flow cytometry Support Protocol 1: Lung preparation Support Protocol 2: Counting cells on a flow cytometer Basic Protocol 2: Surface and intracellular flow cytometry staining Support Protocol 3: Single-color bead controls.</p>","PeriodicalId":11020,"journal":{"name":"Current Protocols in Cytometry","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/cpcy.74","citationCount":"6","resultStr":"{\"title\":\"Acquisition of High-Quality Spectral Flow Cytometry Data.\",\"authors\":\"Amy Fox, Taru S Dutt, Burton Karger, Andrés Obregón-Henao, G Brooke Anderson, Marcela Henao-Tamayo\",\"doi\":\"10.1002/cpcy.74\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Flow cytometry allows the visualization of physical, functional, and/or biological properties of cells including antigens, cytokines, size, and complexity. With increasingly large flow cytometry panels able to analyze up to 50 parameters, there is a need to standardize flow cytometry protocols to achieve high-quality data that can be input into analysis algorithms. Without this clean data, algorithms may incorrectly categorize the cell populations present in the samples. In this protocol, we outline a comprehensive methodology to prepare samples for polychromatic flow cytometry. The use of multiple washing steps and rigorous controls creates high-quality data with good separation between cell populations. Experimental data acquired using this protocol can be analyzed via computational algorithms that perform end-to-end analysis. © 2020 by John Wiley & Sons, Inc. Basic Protocol 1: Preparation of single-cell suspension for flow cytometry Support Protocol 1: Lung preparation Support Protocol 2: Counting cells on a flow cytometer Basic Protocol 2: Surface and intracellular flow cytometry staining Support Protocol 3: Single-color bead controls.</p>\",\"PeriodicalId\":11020,\"journal\":{\"name\":\"Current Protocols in Cytometry\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1002/cpcy.74\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current Protocols in Cytometry\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1002/cpcy.74\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Health Professions\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Protocols in Cytometry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/cpcy.74","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Health Professions","Score":null,"Total":0}
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