NOrMAL

NOrMAL infers precise nucleosome positions and placement probabilities from nucleosome-enriched sequencing data to characterize chromatin organization and nucleosome placement complexity.

Key Features:

• Resolution of overlapping nucleosomes: Employs modeling to resolve closely spaced or overlapping nucleosome configurations that challenge peak-based occupancy methods.
• Placement probability: Reports the probability of placement for each called nucleosome to quantify confidence in positioning.
• Fragment size estimation: Provides estimates of the size of DNA fragments enriched for nucleosomes derived from sequencing data.
• Fuzziness assessment: Assesses whether nucleosome positioning is precise or 'fuzzy' within a sequenced cell sample.
• Robustness to parameters: Demonstrates greater robustness to user-defined parameters compared to Template Filtering on synthetic datasets.
• Sensitivity on real data: Detects a higher number of nucleosomes in real-world datasets, indicating increased sensitivity relative to Template Filtering.

Scientific Applications:

• Genome-wide nucleosome mapping: Enables analysis of genome-wide nucleosome positions from second-generation sequencing data across model organisms.
• Analysis of complex nucleosome configurations: Facilitates study of overlapping and closely spaced nucleosomes that are problematic for traditional occupancy-peak methods.
• Chromatin dynamics and regulation: Supports characterization of nucleosome occupancy, fragment size, and positioning fuzziness to inform studies of chromatin organization and gene regulation.

Methodology:

Uses a parametric probabilistic model with parameters inferred by an expectation maximization algorithm from a mixture of distributions.