rGADEM

rGADEM performs de novo motif discovery and analysis on ChIP-Seq and large-scale genomic sequence datasets to identify co-occurring motifs associated with transcription factor binding.

Key Features:

• Integrated Analysis Pipeline: An R-based pipeline covering data input, peak detection, sequence and motif analysis, visualization, and data export.
• GADEM foundation: Extends the GADEM de novo motif discovery algorithm.
• R implementation: Implemented as an R package for integration with R and Bioconductor workflows.
• Scalability and Performance: Scales to tens of thousands of enriched regions and is optimized for multicore computers.
• Motif Discovery and Analysis: Performs de novo motif discovery and identifies co-occurring motifs with sensitivity to detect motifs aligned with the literature.
• Extensibility: Extensible through incorporation of additional R and Bioconductor packages.
• Visualization and Data Export: Produces sequence and motif visualizations and supports comprehensive data export.

Scientific Applications:

• ChIP-Seq motif discovery: Identification of transcription factor binding motifs from ChIP-Seq datasets and analysis of enriched genomic regions.
• Human transcription factor studies: Demonstrated on human ChIP-Seq datasets for FOXA1, ER, CTCF, and STAT1, recovering motifs consistent with published literature and detecting motifs missed by other methods.

Methodology:

Input of genomic sequence data, peak detection to identify regions of enrichment, sequence and motif analysis for de novo motif discovery and co-occurring motif identification, and generation of visualizations with data export.