Facilitating the Analysis of Immunological Data with Visual Analytic Techniques

被引:6
|
作者
Shih, David C. [1 ,2 ]
Ho, Kevin C. [1 ]
Melnick, Kyle M. [3 ]
Rensink, Ronald A. [2 ,3 ]
Kollmann, Tobias R. [1 ]
Fortuno, Edgardo S. [1 ]
机构
[1] Univ British Columbia, Child & Family Res Inst, Div Infect & Immunol Dis, Dept Paediat, Vancouver, BC V5Z 1M9, Canada
[2] Univ British Columbia, Dept Comp Sci, Vancouver, BC V5Z 1M9, Canada
[3] Univ British Columbia, Dept Psychol, Vancouver, BC V5Z 1M9, Canada
来源
JOVE-JOURNAL OF VISUALIZED EXPERIMENTS | 2011年 / 47期
关键词
Immunology; Issue; 47; Visual analytics; flow cytometry; Luminex; Tableau; cytokine; innate immunity; single nucleotide polymorphism;
D O I
10.3791/2397
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Visual analytics (VA) has emerged as a new way to analyze large dataset through interactive visual display. We demonstrated the utility and the flexibility of a VA approach in the analysis of biological datasets. Examples of these datasets in immunology include flow cytometry, Luminex data, and genotyping (e.g., single nucleotide polymorphism) data. Contrary to the traditional information visualization approach, VA restores the analysis power in the hands of analyst by allowing the analyst to engage in real-time data exploration process. We selected the VA software called Tableau after evaluating several VA tools. Two types of analysis tasks analysis within and between datasets were demonstrated in the video presentation using an approach called paired analysis. Paired analysis, as defined in VA, is an analysis approach in which a VA tool expert works side-by-side with a domain expert during the analysis. The domain expert is the one who understands the significance of the data, and asks the questions that the collected data might address. The tool expert then creates visualizations to help find patterns in the data that might answer these questions. The short lag-time between the hypothesis generation and the rapid visual display of the data is the main advantage of a VA approach.
引用
收藏
页数:6
相关论文
共 50 条
  • [1] Pattern discovery: A progressive visual analytic design to support categorical data analysis
    Zhao, Hanqing
    Zhang, Huijun
    Liu, Yan
    Zhang, Yongzhen
    Zhang, Xiaolong
    JOURNAL OF VISUAL LANGUAGES AND COMPUTING, 2017, 43 : 42 - 49
  • [2] Intelligent Visual Analytic Techniques for Flood Area Mapping Application
    Manavalan
    PROCEEDINGS OF THE 2017 INTERNATIONAL CONFERENCE ON BIG DATA ANALYTICS AND COMPUTATIONAL INTELLIGENCE (ICBDAC), 2017, : 455 - 458
  • [3] Process Data Analysis Using Visual Analytics and Process Mining Techniques
    Sitova, Irina
    Pecerska, Jelena
    2020 61ST INTERNATIONAL SCIENTIFIC CONFERENCE ON INFORMATION TECHNOLOGY AND MANAGEMENT SCIENCE OF RIGA TECHNICAL UNIVERSITY (ITMS), 2020,
  • [4] A Visual Analytic Framework for Data Fusion in Investigative Intelligence
    Cai, Guoray
    Gross, Geoff
    Llinas, James
    Hall, David
    NEXT-GENERATION ANALYST II, 2014, 9122
  • [5] CrystalBall: A Visual Analytic System for Future Event Discovery and Analysis from Social Media Data
    Cho, Isaac
    Wesslen, Ryan
    Volkova, Svitlana
    Ribarsky, William
    Dou, Wenwen
    2017 IEEE CONFERENCE ON VISUAL ANALYTICS SCIENCE AND TECHNOLOGY (VAST), 2017, : 25 - 35
  • [6] SpectrumVA: Visual Analysis of Astronomical Spectra for Facilitating Classification Inspection
    Li, Jincheng
    Lai, Chufan
    Wang, Youfen
    Luo, Ali
    Yuan, Xiaoru
    IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 2024, 30 (08) : 5386 - 5403
  • [7] An Interactive Circular Visual Analytic Tool for Visualization of Web Data
    Dubois, Patrick M. J.
    Han, Zhao
    Jiang, Fan
    Leung, Carson K.
    2016 IEEE/WIC/ACM INTERNATIONAL CONFERENCE ON WEB INTELLIGENCE (WI 2016), 2016, : 709 - 712
  • [8] Data acquisition and visual analytic tool-set for paediatric sleep data
    Vincent, Amal
    Gupta, Ankit
    Li, Ruoyu
    Shaw, Chris
    Akhyani, Saba
    PROCEEDINGS OF THE 13TH EAI INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING TECHNOLOGIES FOR HEALTHCARE (PERVASIVEHEALTH 2019), 2019, : 320 - 326
  • [9] Toward Theoretical Techniques for Measuring the Use of Human Effort in Visual Analytic Systems
    Crouser, R. Jordan
    Franklin, Lyndsey
    Endert, Alex
    Cook, Kris
    IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 2017, 23 (01) : 121 - 130
  • [10] Visual Analytic Tools and Techniques in Population Health and Health Services Research: Scoping Review
    Chishtie, Jawad Ahmed
    Marchand, Jean-Sebastien
    Turcotte, Luke A.
    Bielska, Iwona Anna
    Babineau, Jessica
    Cepoiu-Martin, Monica
    Irvine, Michael
    Munce, Sarah
    Abudiab, Sally
    Bjelica, Marko
    Hossain, Saima
    Imran, Muhammad
    Jeji, Tara
    Jaglal, Susan
    JOURNAL OF MEDICAL INTERNET RESEARCH, 2020, 22 (12)