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TimiRGeN: R/Bioconductor package for time series microRNA–mRNA integration and analysis

MOTIVATION: The analysis of longitudinal datasets and construction of gene regulatory networks (GRNs) provide a valuable means to disentangle the complexity of microRNA (miRNA)–mRNA interactions. However, there are no computational tools that can integrate, conduct functional analysis and generate d...

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Detalles Bibliográficos
Autores principales: Patel, K, Chandrasegaran, S, Clark, I M, Proctor, C J, Young, D A, Shanley, D P
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8545325/
https://www.ncbi.nlm.nih.gov/pubmed/33993215
http://dx.doi.org/10.1093/bioinformatics/btab377
Descripción
Sumario:MOTIVATION: The analysis of longitudinal datasets and construction of gene regulatory networks (GRNs) provide a valuable means to disentangle the complexity of microRNA (miRNA)–mRNA interactions. However, there are no computational tools that can integrate, conduct functional analysis and generate detailed networks from longitudinal miRNA–mRNA datasets. RESULTS: We present TimiRGeN, an R package that uses time point-based differential expression results to identify miRNA–mRNA interactions influencing signaling pathways of interest. miRNA–mRNA interactions can be visualized in R or exported to PathVisio or Cytoscape. The output can be used for hypothesis generation and directing in vitro or further in silico work such as GRN construction. AVAILABILITY AND IMPLEMENTATION: TimiRGeN is available for download on Bioconductor (https://bioconductor.org/packages/TimiRGeN) and requires R v4.0.2 or newer and BiocManager v3.12 or newer. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.