monaLisa：用于识别调控基序的 R/Bioconductor 包。
monaLisa: an R/Bioconductor package for identifying regulatory motifs.
机构信息
Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland.
SIB Swiss Institute of Bioinformatics, Basel, Switzerland.
出版信息
Bioinformatics. 2022 Apr 28;38(9):2624-2625. doi: 10.1093/bioinformatics/btac102.
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.
摘要
与特定核苷酸序列（如转录因子）结合的蛋白质在基因表达调控中发挥着关键作用。它们的结合可以通过相关的转录变化、染色质可及性、DNA 甲基化和组蛋白修饰来间接观察到。确定导致这些观察到的实验变化的候选因子对于理解潜在的生物学过程至关重要。在这里，我们介绍了 monaLisa，这是一个 R/Bioconductor 包，它实现了从实验数据中识别相关转录因子的方法。该软件包可以轻松集成到其他 Bioconductor 包中，并能够在无需 R 以外的任何软件依赖项的情况下进行无缝基序分析。
可用性和实现
monaLisa 是用 R 编写的，可在 Bioconductor 上通过 https://bioconductor.org/packages/monaLisa 访问，其开发版本托管在 GitHub 上的 https://github.com/fmicompbio/monaLisa。
补充信息
补充数据可在 Bioinformatics 在线获取。
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