Cargando…

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...

Descripción completa

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
_version_ 1784695988133298176
author Machlab, Dania
Burger, Lukas
Soneson, Charlotte
Rijli, Filippo M
Schübeler, Dirk
Stadler, Michael B
author_facet Machlab, Dania
Burger, Lukas
Soneson, Charlotte
Rijli, Filippo M
Schübeler, Dirk
Stadler, Michael B
author_sort Machlab, Dania
collection PubMed
description 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.
format Online
Article
Text
id pubmed-9048699
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-90486992022-04-29 monaLisa: an R/Bioconductor package for identifying regulatory motifs Machlab, Dania Burger, Lukas Soneson, Charlotte Rijli, Filippo M Schübeler, Dirk Stadler, Michael B Bioinformatics Applications Notes 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. Oxford University Press 2022-02-23 /pmc/articles/PMC9048699/ /pubmed/35199152 http://dx.doi.org/10.1093/bioinformatics/btac102 Text en © The Author(s) 2022. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Notes
Machlab, Dania
Burger, Lukas
Soneson, Charlotte
Rijli, Filippo M
Schübeler, Dirk
Stadler, Michael B
monaLisa: an R/Bioconductor package for identifying regulatory motifs
title monaLisa: an R/Bioconductor package for identifying regulatory motifs
title_full monaLisa: an R/Bioconductor package for identifying regulatory motifs
title_fullStr monaLisa: an R/Bioconductor package for identifying regulatory motifs
title_full_unstemmed monaLisa: an R/Bioconductor package for identifying regulatory motifs
title_short monaLisa: an R/Bioconductor package for identifying regulatory motifs
title_sort monalisa: an r/bioconductor package for identifying regulatory motifs
topic Applications Notes
url 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
work_keys_str_mv AT machlabdania monalisaanrbioconductorpackageforidentifyingregulatorymotifs
AT burgerlukas monalisaanrbioconductorpackageforidentifyingregulatorymotifs
AT sonesoncharlotte monalisaanrbioconductorpackageforidentifyingregulatorymotifs
AT rijlifilippom monalisaanrbioconductorpackageforidentifyingregulatorymotifs
AT schubelerdirk monalisaanrbioconductorpackageforidentifyingregulatorymotifs
AT stadlermichaelb monalisaanrbioconductorpackageforidentifyingregulatorymotifs