Advantages of CEMiTool for gene co-expression analysis of RNA-seq data.
Comput Biol Med
; 125: 103975, 2020 10.
Article
em En
| MEDLINE
| ID: mdl-32911277
ABSTRACT
Gene co-expression analysis is widely applied to transcriptomics data to associate clusters of genes with biological functions or identify therapeutic targets in diseases. Recently, the emergence of high-throughput technologies for gene expression analyses allows researchers to establish connections through gene co-expression analysis to identify clinical disease markers. However, gene co-expression analysis is complex and may be a daunting task. Here, we evaluate three co-expression analysis packages (WGCNA, CEMiTool, and coseq) using published RNA-seq datasets derived from ischemic cardiomyopathy and chronic obstructive pulmonary disease. Results show that the packages produced consensus co-expression clusters using default parameters. CEMiTool package outperformed the other two packages and required less computational resource and bioinformatics experience. This evaluation provides a basis on which data analysts can select bioinformatics tools for gene co-expression analysis.
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1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Biologia Computacional
/
Perfilação da Expressão Gênica
Idioma:
En
Revista:
Comput Biol Med
Ano de publicação:
2020
Tipo de documento:
Article