MoDentify: phenotype-driven module identification in metabolomics networks at different resolutions.
Bioinformatics
; 35(3): 532-534, 2019 02 01.
Article
em En
| MEDLINE
| ID: mdl-30032270
ABSTRACT
Summary:
Associations of metabolomics data with phenotypic outcomes are expected to span functional modules, which are defined as sets of correlating metabolites that are coordinately regulated. Moreover, these associations occur at different scales, from entire pathways to only a few metabolites; an aspect that has not been addressed by previous methods. Here, we present MoDentify, a free R package to identify regulated modules in metabolomics networks at different layers of resolution. Importantly, MoDentify shows higher statistical power than classical association analysis. Moreover, the package offers direct interactive visualization of the results in Cytoscape. We present an application example using complex, multifluid metabolomics data. Due to its generic character, the method is widely applicable to other types of data. Availability and implementation https//github.com/krumsieklab/MoDentify (vignette includes detailed workflow). Supplementary information Supplementary data are available at Bioinformatics online.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Software
/
Biologia Computacional
/
Metabolômica
Tipo de estudo:
Diagnostic_studies
Idioma:
En
Revista:
Bioinformatics
Assunto da revista:
INFORMATICA MEDICA
Ano de publicação:
2019
Tipo de documento:
Article
País de afiliação:
Alemanha