DiffChIPL

DiffChIPL performs differential peak analysis of high-throughput chromatin profiling datasets (ChIP-seq, CUT&RUN, CUT&Tag, ATAC-seq) to detect changes in transcription factor binding, histone modifications, and chromatin accessibility across biological replicates.

Key Features:

• Adaptive Analysis: Handles both asymmetrical and symmetrical data distributions to report global differences across datasets.
• Improved Sensitivity and Specificity: Demonstrates superior sensitivity and lower false positive rates validated using extensive simulations and control datasets.
• Versatility Across Data Types: Applicable to ChIP-seq, CUT&RUN, CUT&Tag, and ATAC-seq for analysis of transcription factors, histone modifications, and chromatin accessibility.
• Robust Performance: Validated on simulated and real datasets to provide consistent differential peak detection across biological contexts.

Scientific Applications:

• Transcription Factor Binding: Detects differential binding events of transcription factors across conditions or treatments.
• Histone Modification Analysis: Identifies differential histone modification peaks between experimental groups.
• Chromatin Accessibility: Detects changes in chromatin accessibility using ATAC-seq, CUT&RUN, or CUT&Tag data.

Methodology:

Implements the Limma (Linear Models for Microarray Data) statistical framework adapted for ChIP-seq and related datasets to account for variability and noise in biological replicates.