Metabox: A Toolbox for Metabolomic Data Analysis, Interpretation and Integrative Exploration

被引:68
|
作者
Wanichthanarak, Kwanjeera [1 ]
Fan, Sili [1 ]
Grapov, Dmitry [1 ]
Barupal, Dinesh Kumar [1 ]
Fiehn, Oliver [1 ,2 ]
机构
[1] Univ Calif Davis, Genome Ctr, West Coast Metab Ctr, Davis, CA 95616 USA
[2] King Abdulaziz Univ, Dept Biochem, Jeddah, Saudi Arabia
来源
PLOS ONE | 2017年 / 12卷 / 01期
基金
美国国家卫生研究院;
关键词
GENE-EXPRESSION; O-GLCNAC; VISUALIZATION; INFORMATION; NETWORKS;
D O I
10.1371/journal.pone.0171046
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
Similar to genomic and proteomic platforms, metabolomic data acquisition and analysis is becoming a routine approach for investigating biological systems. However, computational approaches for metabolomic data analysis and integration are still maturing. Metabox is a bioinformatics toolbox for deep phenotyping analytics that combines data processing, statistical analysis, functional analysis and integrative exploration of metabolomic data within proteomic and transcriptomic contexts. With the number of options provided in each analysis module, it also supports data analysis of other `omic' families. The toolbox is an R-based web application, and it is freely available at http://kvvanjeeraw.gthub.io/metabox/undertheGPL-3 license.
引用
收藏
页数:14
相关论文
共 50 条
  • [1] Giotto: a toolbox for integrative analysis and visualization of spatial expression data
    Dries, Ruben
    Zhu, Qian
    Dong, Rui
    Eng, Chee-Huat Linus
    Li, Huipeng
    Liu, Kan
    Fu, Yuntian
    Zhao, Tianxiao
    Sarkar, Arpan
    Bao, Feng
    George, Rani E.
    Pierson, Nico
    Cai, Long
    Yuan, Guo-Cheng
    GENOME BIOLOGY, 2021, 22 (01)
  • [2] RGT: a toolbox for the integrative analysis of high throughput regulatory genomics data
    Li, Zhijian
    Kuo, Chao-Chung
    Ticconi, Fabio
    Shaigan, Mina
    Gehrmann, Julia
    Gusmao, Eduardo Gade
    Allhoff, Manuel
    Manolov, Martin
    Zenke, Martin
    Costa, Ivan G.
    BMC BIOINFORMATICS, 2023, 24 (01)
  • [3] RGT: a toolbox for the integrative analysis of high throughput regulatory genomics data
    Zhijian Li
    Chao-Chung Kuo
    Fabio Ticconi
    Mina Shaigan
    Julia Gehrmann
    Eduardo Gade Gusmao
    Manuel Allhoff
    Martin Manolov
    Martin Zenke
    Ivan G. Costa
    BMC Bioinformatics, 24
  • [4] A toolbox to explore NMR metabolomic data sets using the R environment
    Balayssac, Stephane
    Dejean, Sebastien
    Lalande, Julie
    Gilard, Veronique
    Malet-Martino, Myriam
    CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2013, 126 : 50 - 59
  • [5] Pathway-directed weighted testing procedures for the integrative analysis of gene expression and metabolomic data
    Poisson, Laila M.
    Sreekumar, Arun
    Chinnaiyan, Arul M.
    Ghosh, Debashis
    GENOMICS, 2012, 99 (05) : 265 - 274
  • [6] An integrative data analysis platform for gene set analysis and knowledge discovery in a data warehouse framework
    Chen, Yi-An
    Tripathi, Lokesh P.
    Mizuguchi, Kenji
    DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION, 2016,
  • [7] Dynamic metabolomic data analysis: a tutorial review
    Smilde, A. K.
    Westerhuis, J. A.
    Hoefsloot, H. C. J.
    Bijlsma, S.
    Rubingh, C. M.
    Vis, D. J.
    Jellema, R. H.
    Pijl, H.
    Roelfsema, F.
    van der Greef, J.
    METABOLOMICS, 2010, 6 (01) : 3 - 17
  • [8] Nicotiana attenuata Data Hub (NaDH): an integrative platform for exploring genomic, transcriptomic and metabolomic data in wild tobacco
    Brockmoeller, Thomas
    Ling, Zhihao
    Li, Dapeng
    Gaquerel, Emmanuel
    Baldwin, Ian T.
    Xu, Shuqing
    BMC GENOMICS, 2017, 18
  • [9] Exploratory analysis of high-throughput metabolomic data
    Wijetunge, Chalini D.
    Li, Zhaoping
    Saeed, Isaam
    Bowne, Jairus
    Hsu, Arthur L.
    Roessner, Ute
    Bacic, Antony
    Halgamuge, Saman K.
    METABOLOMICS, 2013, 9 (06) : 1311 - 1320
  • [10] MICAA toolbox for masked independent component analysis of fMRI data
    Alsady, Tawfik Moher
    Blessing, Esther M.
    Beissner, Florian
    HUMAN BRAIN MAPPING, 2016, 37 (10) : 3544 - 3556