Enhancing Interpretability of Gene Signatures with Prior Biological Knowledge.
Microarrays (Basel)
; 5(2)2016 Jun 08.
Article
em En
| MEDLINE
| ID: mdl-27600081
ABSTRACT
Biological interpretability is a key requirement for the output of microarray data analysis pipelines. The most used pipeline first identifies a gene signature from the acquired measurements and then uses gene enrichment analysis as a tool for functionally characterizing the obtained results. Recently Knowledge Driven Variable Selection (KDVS), an alternative approach which performs both steps at the same time, has been proposed. In this paper, we assess the effectiveness of KDVS against standard approaches on a Parkinson's Disease (PD) dataset. The presented quantitative analysis is made possible by the construction of a reference list of genes and gene groups associated to PD. Our work shows that KDVS is much more effective than the standard approach in enhancing the interpretability of the obtained results.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
Microarrays (Basel)
Ano de publicação:
2016
Tipo de documento:
Article
País de afiliação:
Itália