monaLisa

monaLisa implements approaches to identify relevant transcription factors from experimental data by working with sequence motifs in the analysis of genomics data.

Key Features:

• Motif annotation: Methods annotate genomic regions or sequences with predicted motif hits.
• Motif identification: Identifies motifs that drive observed changes in accessibility or expression.
• Visualization: Functions produce informative visualizations of the obtained results.
• Integration: The package can be integrated with other Bioconductor packages for seamless motif analyses.

Scientific Applications:

• Transcription factor identification: Identifies candidate transcription factors responsible for observed experimental changes in transcription, chromatin accessibility, DNA methylation, and histone modifications.
• Gene expression regulation analysis: Identifies regulatory motifs underlying biological processes controlling gene expression.

Methodology:

Binned motif enrichment analysis.