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monaLisa: an R/Bioconductor package for identifying regulatory motifs.
Machlab, Dania; Burger, Lukas; Soneson, Charlotte; Rijli, Filippo M; Schübeler, Dirk; Stadler, Michael B.
Afiliação
  • Machlab D; Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland.
  • Burger L; SIB Swiss Institute of Bioinformatics, Basel, Switzerland.
  • Soneson C; Faculty of Science, University of Basel, Basel, Switzerland.
  • Rijli FM; Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland.
  • Schübeler D; SIB Swiss Institute of Bioinformatics, Basel, Switzerland.
  • Stadler MB; Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland.
Bioinformatics ; 38(9): 2624-2625, 2022 04 28.
Article em En | MEDLINE | ID: mdl-35199152
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.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Fatores de Transcrição / Software Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Fatores de Transcrição / Software Idioma: En Ano de publicação: 2022 Tipo de documento: Article