{"title":"PolarFCS: A Multi-Parametric Data Visualisation Aid for Flow Cytometry Assessment","authors":"Pavandeep Gill, J. Luider, E. Mahé","doi":"10.14806/EJ.23.0.892","DOIUrl":null,"url":null,"abstract":"Currently available Flow-Cytometry Software (FCS) analysis platforms are computationally efficient and user-friendly, but may lack the functionality of single-plot, multi-parametric data visualisation. Methods to overcome this include gating techniques and/or dimensionality reduction. However, these strategies make Flow-Cytometry (FC) data analysis more time- and labour-intensive; profound errors can also result from incorrect FCS use. We have developed PolarFCS, a software tool capable of single-plot, multi-parametric data visualisation. Unlike traditional clinical FC plots, which typically operate directly on a data-set to produce single-parameter FC histograms or two-parameter orthogonal scatter plots, PolarFCS operates on the flow-parameter calculated centre of mass of each event in the data-set, and presents these as a dot-plot. We compare PolarFCS to our traditional clinical FCS workflow, using a selection of clinical plasma cell FC data. Multiple flow plots and gating strategies are required in the traditional software to isolate neoplastic populations. In PolarFCS, however, positional re-arrangement and scaling of the poles can be used to quickly isolate a population of interest. We also compare both approaches in a case of Minimal Residual Disease (MRD) assessment, and again, the versatility of the polar adjustment and parameter scaling allowable with PolarFCS is demonstrated. PolarFCS employs strategies that allow more accurate, standardised and detailed FC data analysis compared to traditional FCS platforms. Visualisation of multiple parameters in a single plot is an effective and invaluable feature that many other platforms currently do not offer. Availability: PolarFCS can be downloaded at https://github.com/etiennemahe/PolarFCS","PeriodicalId":72893,"journal":{"name":"EMBnet.journal","volume":"58 1","pages":"892"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"EMBnet.journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14806/EJ.23.0.892","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Currently available Flow-Cytometry Software (FCS) analysis platforms are computationally efficient and user-friendly, but may lack the functionality of single-plot, multi-parametric data visualisation. Methods to overcome this include gating techniques and/or dimensionality reduction. However, these strategies make Flow-Cytometry (FC) data analysis more time- and labour-intensive; profound errors can also result from incorrect FCS use. We have developed PolarFCS, a software tool capable of single-plot, multi-parametric data visualisation. Unlike traditional clinical FC plots, which typically operate directly on a data-set to produce single-parameter FC histograms or two-parameter orthogonal scatter plots, PolarFCS operates on the flow-parameter calculated centre of mass of each event in the data-set, and presents these as a dot-plot. We compare PolarFCS to our traditional clinical FCS workflow, using a selection of clinical plasma cell FC data. Multiple flow plots and gating strategies are required in the traditional software to isolate neoplastic populations. In PolarFCS, however, positional re-arrangement and scaling of the poles can be used to quickly isolate a population of interest. We also compare both approaches in a case of Minimal Residual Disease (MRD) assessment, and again, the versatility of the polar adjustment and parameter scaling allowable with PolarFCS is demonstrated. PolarFCS employs strategies that allow more accurate, standardised and detailed FC data analysis compared to traditional FCS platforms. Visualisation of multiple parameters in a single plot is an effective and invaluable feature that many other platforms currently do not offer. Availability: PolarFCS can be downloaded at https://github.com/etiennemahe/PolarFCS