OccuPeak

OccuPeak calls enriched regions (peaks) from ChIP-seq data by constructing an internal background model to enable sensitive detection of enhancers and transcription factor occupancy.

Key Features:

• Internal Background Modelling: Accounts for GC-content deviations between Input-seq and ChIP-seq by constructing a background model from overlapping single reads and abundant low-frequency tags within each ChIP-seq dataset, removing the need for additional control datasets.
• Excess Ratio Metric: Uses an excess ratio metric that measures peak significance based on peak tag density and global noise levels.
• High Sensitivity and Performance: Demonstrates higher sensitivity in enhancer identification benchmarks compared with MACS and CisGenome and shows comparable overlap with DNase I hypersensitive sites and H3K27ac sites for transcription factor occupation.
• Clinical Relevance: Calls peaks that are significantly enriched for single nucleotide polymorphisms (SNPs) associated with cardiac diseases.

Scientific Applications:

• Transcriptional regulation and epigenetics: Generation of ChIP-seq peak maps for studies of transcriptional regulation and epigenetic modifications.
• Enhancer identification: Sensitive detection of enhancers from ChIP-seq datasets as demonstrated in comparative benchmarks.
• Disease-associated variant interpretation: Prioritization and enrichment analysis of disease-associated SNPs, including cardiac disease variants.

Methodology:

Constructs an internal background by leveraging overlapping single reads and low-frequency tags within each ChIP-seq dataset and computes an excess ratio metric based on tag density and global noise levels to score peaks.