NarrowPeaks

NarrowPeaks applies functional principal component analysis (FPCA) to postprocess ChIP-seq peak-caller output and characterize differential variation across read-enriched regions and replicates.

Key Features:

• Functional Principal Component Analysis (FPCA): Implements a functional version of principal component analysis to decompose variance within ChIP-seq read-enriched regions.
• Postprocessing of peak-caller output: Operates on data typically produced by generic ChIP-seq peak callers, including wiggle track format.
• Read-enriched region analysis: Analyzes ChIP-seq peaks and read-enriched regions to extract signal profiles for downstream variance analysis.
• Differential variation across samples and replicates: Quantifies and highlights differential variation between multiple ChIP-seq samples with replicates.
• Detection of subtle variance-driven patterns: Identifies variance patterns within regions that may be missed by traditional analysis methods.

Scientific Applications:

• Transcription factor complex analysis: Supports analysis of TF complexes such as MADS-box proteins FLOWERING LOCUS C (FLC) and SHORT VEGETATIVE PHASE (SVP) to dissect individual versus complex binding effects.
• Regulatory network mapping: Aids identification of genes whose regulation depends on simultaneous action of multiple proteins, informing regulatory network reconstruction.
• Genome-wide regulatory code characterization: Enables genome-wide analysis of TF-controlled regulatory codes, including DNA-binding flexibility and robustness relevant to processes like flowering initiation in Arabidopsis.

Methodology:

Applies functional principal component analysis (FPCA) to postprocess ChIP-seq peak-caller output (e.g., wiggle track format) and quantify differential variation across read-enriched regions and replicates.