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...
Autores principales: | , , , , , |
---|---|
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 |