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DEGGs: an R package with shiny app for the identification of differentially expressed gene–gene interactions in high-throughput sequencing data
SUMMARY: The discovery of differential gene–gene correlations across phenotypical groups can help identify the activation/deactivation of critical biological processes underlying specific conditions. The presented R package, provided with a count and design matrix, extract networks of group-specific...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10133399/ https://www.ncbi.nlm.nih.gov/pubmed/37084249 http://dx.doi.org/10.1093/bioinformatics/btad192 |
Sumario: | SUMMARY: The discovery of differential gene–gene correlations across phenotypical groups can help identify the activation/deactivation of critical biological processes underlying specific conditions. The presented R package, provided with a count and design matrix, extract networks of group-specific interactions that can be interactively explored through a shiny user-friendly interface. For each gene–gene link, differential statistical significance is provided through robust linear regression with an interaction term. AVAILABILITY AND IMPLEMENTATION: DEGGs is implemented in R and available on GitHub at https://github.com/elisabettasciacca/DEGGs. The package is also under submission on Bioconductor. |
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