GiANT: gene set uncertainty in enrichment analysis.
Bioinformatics
; 32(12): 1891-4, 2016 06 15.
Article
em En
| MEDLINE
| ID: mdl-26833345
ABSTRACT
UNLABELLED Over the past years growing knowledge about biological processes and pathways revealed complex interaction networks involving many genes. In order to understand these networks, analysis of differential expression has continuously moved from single genes towards the study of gene sets. Various approaches for the assessment of gene sets have been developed in the context of gene set analysis (GSA). These approaches are bridging the gap between raw measurements and semantically meaningful terms.We present a novel approach for assessing uncertainty in the definition of gene sets. This is an essential step when new gene sets are constructed from domain knowledge or given gene sets are suspected to be affected by uncertainty. Quantification of uncertainty is implemented in the R-package GiANT. We also included widely used GSA methods, embedded in a generic framework that can readily be extended by custom methods. The package provides an easy to use front end and allows for fast parallelization. AVAILABILITY AND IMPLEMENTATION The package GiANT is available on CRAN. CONTACTS hans.kestler@leibniz-fli.de or hans.kestler@uni-ulm.de.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Software
/
Incerteza
/
Redes Reguladoras de Genes
Limite:
Animals
/
Humans
Idioma:
En
Revista:
Bioinformatics
Assunto da revista:
INFORMATICA MEDICA
Ano de publicação:
2016
Tipo de documento:
Article
País de afiliação:
Alemanha