explorase: Multivariate exploratory analysis and visualization for systems biology

被引:0
|
作者
Lawrence, Michael [1 ]
Cook, Dianne [2 ]
Lee, Eun-Kyung [3 ]
Babka, Heather [2 ]
Wurtele, Eve Syrkin [2 ]
机构
[1] Fred Hutchinson Canc Res Ctr, Div Publ Hlth Sci, Program Computat Biol, Seattle, WA 98104 USA
[2] Iowa State Univ, Ames, IA 50011 USA
[3] Univ Ulsan, Ulsan, South Korea
来源
JOURNAL OF STATISTICAL SOFTWARE | 2008年 / 25卷 / 09期
关键词
bioconductor; bioinformatics; microarray; graphical user interface; exploratory data analysis; interactive graphics; visualization; metabolomics; proteomics;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The datasets being produced by high-throughput biological experiments, such as microarrays, have forced biologists to turn to sophisticated statistical analysis and visualization tools in order to understand their data. We address the particular need for an open-source exploratory data analysis tool that applies numerical methods in coordination with interactive graphics to the analysis of experimental data. The software package, known as explorase, provides a graphical user interface (GUI) on top of the R platform for statistical computing and the GGobi software for multivariate interactive graphics. The GUI is designed for use by biologists, many of whom are unfamiliar with the R language. It displays metadata about experimental design and biological entities in tables that are sortable and filterable. There are menu shortcuts to the analysis methods implemented in R, including graphical interfaces to linear modeling tools. The GUI is linked to data plots in GGobi through a brush tool that simultaneously colors rows in the entity information table and points in the GGobi plots. explorase is an R package publicly available from Bioconductor and is a tool in the MetNet platform for the analysis of systems biology data.
引用
收藏
页码:1 / 23
页数:23
相关论文
共 50 条
  • [41] BiomMiner: An advanced exploratory microbiome analysis and visualization pipeline
    Shamsaddini, Amirhossein
    Dadkhah, Kimia
    Gillevet, Patrick M.
    [J]. PLOS ONE, 2020, 15 (06):
  • [42] SEE: a tool for the visualization and analysis of rodent exploratory behavior
    Drai, D
    Golani, I
    [J]. NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS, 2001, 25 (05): : 409 - 426
  • [43] Using Convex Sets for Exploratory Data Analysis and Visualization
    Wojciech Grohman
    [J]. Data Mining and Knowledge Discovery, 2004, 9 (3) : 275 - 295
  • [44] Interactive information visualization for exploratory intelligence data analysis
    Risch, J
    May, R
    Thomas, J
    Dowson, S
    [J]. PROCEEDINGS OF THE IEEE 1996 VIRTUAL REALITY ANNUAL INTERNATIONAL SYMPOSIUM, 1996, : 230 - &
  • [45] The Interactive Visualization Gap in Initial Exploratory Data Analysis
    Batch, Andrea
    Elmqvist, Niklas
    [J]. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 2018, 24 (01) : 278 - 287
  • [46] Longitudinal visualization for exploratory analysis of multiple sclerosis lesions
    Sugathan, Sherin
    Bartsch, Hauke
    Riemer, Frank
    Gruner, Renate
    Lawonn, Kai
    Smit, Noeska
    [J]. COMPUTERS & GRAPHICS-UK, 2022, 107 : 208 - 219
  • [47] Using convex sets for exploratory data analysis and visualization
    Grohman, W
    [J]. DATA MINING AND KNOWLEDGE DISCOVERY, 2004, 9 (03) : 275 - 295
  • [48] UCSF chimera - A visualization system for exploratory research and analysis
    Pettersen, EF
    Goddard, TD
    Huang, CC
    Couch, GS
    Greenblatt, DM
    Meng, EC
    Ferrin, TE
    [J]. JOURNAL OF COMPUTATIONAL CHEMISTRY, 2004, 25 (13) : 1605 - 1612
  • [49] Multivariate data visualization for qualitative model choice in learning systems
    Grishin, V
    [J]. JOINT CONFERENCE ON THE SCIENCE AND TECHNOLOGY OF INTELLIGENT SYSTEMS, 1998, : 622 - 627
  • [50] Analysis and visualization of category membership distribution in multivariate data
    Pao, YH
    Duan, BF
    Zhao, YL
    LeClair, SR
    [J]. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2000, 13 (05) : 521 - 525