CRUNCH

CRUNCH analyzes ChIP-seq data to process raw sequencing reads through quality control, read mapping, fragment size estimation, peak calling, peak annotation, and comprehensive regulatory motif analysis.

Key Features:

• Automated Workflow: Executes sequential processing from raw sequencing reads through quality control, read mapping, fragment size estimation, peak calling, peak annotation, and motif analysis.
• Standardization Across Experiments: Provides a consistent computational framework enabling meaningful comparisons across experiments and cell lines.
• Comprehensive Motif Analysis: Integrates modeling of ChIP signals to quantify the contribution of each motif and to annotate combinations of motifs that explain binding peaks.
• Identification of TF Categories: Classifies transcription factors into 'solitary TFs' where a single motif explains ChIP peaks and 'co-binding TFs' characterized by co-occurrence of multiple motifs within peaks.
• Performance and Consistency: On 128 ENCODE datasets, de novo identified motifs often outperform known motifs and the approach consistently identifies co-binding motif sets and top motifs for solitary TFs across experiments and cell lines.

Scientific Applications:

• Transcription factor binding analysis: Quantifies motif contributions and motif combinations to interpret TF binding patterns from ChIP-seq peaks.
• Regulatory network inference: Provides detailed motif analyses that aid in deciphering complex regulatory networks and gene regulation mechanisms.
• Comparative ChIP-seq analysis: Standardized processing enables reproducible comparisons across experiments, conditions, and cell lines.

Methodology:

Performs quality control, read mapping, fragment size estimation, peak calling, peak annotation, de novo and known motif analysis, models ChIP signals to quantify motif contributions and motif combinations, and classifies TFs into solitary versus co-binding categories.