Abstract
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.
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CITATION STYLE
Machlab, D., Burger, L., Soneson, C., Rijli, F. M., Schübeler, D., & Stadler, M. B. (2022). monaLisa: An R/Bioconductor package for identifying regulatory motifs. Bioinformatics, 38(9), 2624–2625. https://doi.org/10.1093/bioinformatics/btac102
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