Phantom: investigating heterogeneous gene sets in time-course data.
Bioinformatics
; 33(18): 2957-2959, 2017 Sep 15.
Article
em En
| MEDLINE
| ID: mdl-28595310
ABSTRACT
MOTIVATION Gene set analysis is a powerful tool to study the coordinative change of time-course data. However, most existing methods only model the overall change of a gene set, yet completely overlooked heterogeneous time-dependent changes within sub-sets of genes. RESULTS:
We have developed a novel statistical method, Phantom, to investigate gene set heterogeneity. Phantom employs the principle of multi-objective optimization to assess the heterogeneity inside a gene set, which also accounts for the temporal dependency in time-course data. Phantom improves the performance of gene set based methods to detect biological changes across time. AVAILABILITY AND IMPLEMENTATION Phantom webpage can be accessed at http//www.baylorhealth.edu/Phantom . R package of Phantom is available at https//cran.r-project.org/web/packages/phantom/index.html . CONTACT jinghua.gu@bswhealth.org. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Software
/
Regulação da Expressão Gênica
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Biologia Computacional
/
Modelos Genéticos
Limite:
Humans
Idioma:
En
Ano de publicação:
2017
Tipo de documento:
Article