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ABSTRACT: 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.
SUBMITTER: Machlab D
PROVIDER: S-EPMC9048699 | biostudies-literature | 2022 Apr
REPOSITORIES: biostudies-literature
Machlab Dania D Burger Lukas L Soneson Charlotte C Rijli Filippo M FM Schübeler Dirk D Stadler Michael B MB
Bioinformatics (Oxford, England) 20220401 9
<h4>Summary</h4>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 ...[more]