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monaLisa: an R/Bioconductor package for identifying regulatory motifs

SUMMARY: Proteins binding to specific nucleotide sequences, such as transcription factors, play key roles in the regulation of gene expression. Their binding can be indirectly observed via associated changes in transcription, chromatin accessibility, DNA methylation and histone modifications. Identi...

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Detalles Bibliográficos
Autores principales: Machlab, Dania, Burger, Lukas, Soneson, Charlotte, Rijli, Filippo M, Schübeler, Dirk, Stadler, Michael B
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9048699/
https://www.ncbi.nlm.nih.gov/pubmed/35199152
http://dx.doi.org/10.1093/bioinformatics/btac102
Descripción
Sumario:SUMMARY: Proteins binding to specific nucleotide sequences, such as transcription factors, play key roles in the regulation of gene expression. Their binding can be indirectly observed via associated changes in transcription, chromatin accessibility, DNA methylation and histone modifications. Identifying candidate factors that are responsible for these observed experimental changes is critical to understand the underlying biological processes. Here, we present monaLisa, an R/Bioconductor package that implements approaches to identify relevant transcription factors from experimental data. The package can be easily integrated with other Bioconductor packages and enables seamless motif analyses without any software dependencies outside of R. AVAILABILITY AND IMPLEMENTATION: monaLisa is implemented in R and available on Bioconductor at https://bioconductor.org/packages/monaLisa with the development version hosted on GitHub at https://github.com/fmicompbio/monaLisa. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.