Metabox: A toolbox for metabolomic data analysis, interpretation and integrative exploration

Kwanjeera Wanichthanarak; Sili Fan; Dmitry Grapov; Dinesh Kumar Barupal; Oliver Fiehn

doi:10.1371/journal.pone.0171046

Metabox: A toolbox for metabolomic data analysis, interpretation and integrative exploration

Kwanjeera Wanichthanarak, Sili Fan, Dmitry Grapov, Dinesh Kumar Barupal, Oliver Fiehn

Molecular and Cellular Biology

Research output: Contribution to journal › Article

43 Scopus citations

Abstract

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://kwanjeeraw.github.io/metabox/under the GPL-3 license.

Original language	English (US)
Article number	e0171046
Journal	PLoS One
Volume	12
Issue number	1
DOIs	https://doi.org/10.1371/journal.pone.0171046
State	Published - Jan 1 2017

Fingerprint

ASJC Scopus subject areas

Medicine(all)
Biochemistry, Genetics and Molecular Biology(all)
Agricultural and Biological Sciences(all)

Cite this

Wanichthanarak, K., Fan, S., Grapov, D., Barupal, D. K., & Fiehn, O. (2017). Metabox: A toolbox for metabolomic data analysis, interpretation and integrative exploration. PLoS One, 12(1), [e0171046]. https://doi.org/10.1371/journal.pone.0171046

@article{e9a331a764e4433da261ff500a42494e,

title = "Metabox: A toolbox for metabolomic data analysis, interpretation and integrative exploration",

abstract = "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://kwanjeeraw.github.io/metabox/under the GPL-3 license.",

author = "Kwanjeera Wanichthanarak and Sili Fan and Dmitry Grapov and Barupal, {Dinesh Kumar} and Oliver Fiehn",

year = "2017",

month = jan

day = "1",

doi = "10.1371/journal.pone.0171046",

language = "English (US)",

volume = "12",

journal = "PLoS One",

issn = "1932-6203",

publisher = "Public Library of Science",

number = "1",

}

TY - JOUR

T1 - Metabox

T2 - A toolbox for metabolomic data analysis, interpretation and integrative exploration

AU - Wanichthanarak, Kwanjeera

AU - Fan, Sili

AU - Grapov, Dmitry

AU - Barupal, Dinesh Kumar

AU - Fiehn, Oliver

PY - 2017/1/1

Y1 - 2017/1/1

N2 - 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://kwanjeeraw.github.io/metabox/under the GPL-3 license.

AB - 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://kwanjeeraw.github.io/metabox/under the GPL-3 license.

UR - http://www.scopus.com/inward/record.url?scp=85011275765&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85011275765&partnerID=8YFLogxK

U2 - 10.1371/journal.pone.0171046

DO - 10.1371/journal.pone.0171046

M3 - Article

AN - SCOPUS:85011275765

VL - 12

JO - PLoS One

JF - PLoS One

SN - 1932-6203

IS - 1

M1 - e0171046

ER -

Access to Document

10.1371/journal.pone.0171046