SEMplMe

SEMplMe predicts the effects of DNA methylation on transcription factor binding affinity at every position within a transcription factor's motif.

Key Features:

• Integration with Methylation Data: Integrates DNA methylation data into predictions of transcription factor binding strength.
• Comprehensive Positional Analysis: Predicts the impact of methylation at each position within a transcription factor motif.
• Validation of Methylation Sensitivity: Validates known methylation-sensitive and methylation-insensitive positions.
• Cell Type Specific Insights: Identifies cell type-specific transcription factor binding events influenced by methylation.
• Performance Superiority: Outperforms SELEX-based (Systematic Evolution of Ligands by Exponential Enrichment) predictions for the CTCF transcription factor.

Scientific Applications:

• Identification of disease-associated methylation sites: Pinpoints aberrant DNA methylation sites that alter transcription factor binding and may contribute to human diseases.
• Insights into tissue-specific regulation and targets: Elucidates methylation-driven, tissue-specific gene regulatory events and supports identification of candidate therapeutic targets.

Methodology:

SEMplMe uses ChIP-seq (Chromatin Immunoprecipitation Sequencing) and whole genome bisulfite sequencing datasets to predict how DNA methylation affects transcription factor binding within motifs.