Serpentine

Serpentine applies adaptive two-dimensional binning to differential Hi-C contact maps to reduce noise in low-signal regions and preserve informative chromatin contacts for improved interpretation of 3D genome organization from deep sequencing-derived contact frequencies.

Key Features:

• Adaptive 2D Binning Methodology: Employs a two-dimensional binning approach that selectively bins only regions identified as noisy in Hi-C contact maps.
• Noise Reduction in Low-Signal Regions: Performs local smearing to manage the multi-fractal distribution of contact frequencies and improve signal-to-noise ratio in distant or poorly covered regions such as repeated sequences.
• Preservation of Informative Data: Maintains high-quality, non-noisy regions of contact maps by avoiding indiscriminate binning and preserving informative contact patterns.
• High-Quality Visualization: Produces refined contact maps optimized for visualization and comparative analyses of chromatin organization.

Scientific Applications:

• Genomics and Epigenetics: Facilitates analysis of 3D genome architecture from Hi-C contact frequencies for studies in genomics and epigenetics.
• Gene Regulation Studies: Supports interpretation of chromatin folding effects on gene regulation by providing cleaner contact maps.
• Chromosomal Abnormality Investigation: Aids investigation of chromosomal abnormalities by enhancing detection of differential contacts in noisy regions.
• Comparative Hi-C Analyses: Enables comparative analyses across contact maps by reducing noise-driven artifacts while preserving informative signals.

Methodology:

Operates on raw Hi-C data by analyzing each region of the contact map to determine necessity of binning based on set noise thresholds, selectively applying adaptive two-dimensional binning and local smearing to low signal-to-noise regions; functionality is implemented in functions such as sp.serpentin_binning which accept input matrices and threshold parameters.