hicrep

hicrep computes the stratum adjusted correlation coefficient (SCC) to assess reproducibility between Hi-C interaction/contact matrices by adjusting for spatial features such as domain structures and distance-dependent interactions.

Key Features:

• Stratum Adjusted Correlation Coefficient (SCC): A similarity metric that quantifies concordance between Hi-C interaction matrices.
• Spatial-feature adjustment: Accounts for domain structures and distance-dependent interactions inherent in Hi-C data during similarity assessment.
• Reproducibility discrimination: Detects subtle differences in data reproducibility across Hi-C datasets.
• Matrix comparison and quantification: Measures differences between Hi-C contact matrices for comparative analyses.
• Sequencing depth assessment: Facilitates determination of required sequencing depth to achieve a target resolution.
• Genome-wide chromatin interaction focus: Operates on genome-wide Hi-C contact matrices for chromatin conformation studies.
• Quality-control metric: Provides a quantitative measure applicable to reproducibility-based quality control of Hi-C experiments.

Scientific Applications:

• Hi-C reproducibility assessment: Evaluates reproducibility of Hi-C experiments by comparing contact matrices using SCC.
• Comparative Hi-C analysis: Quantifies differences between Hi-C contact matrices for inter-sample or inter-condition comparisons.
• Sequencing depth and resolution planning: Estimates optimal sequencing depth required to reach a desired contact-map resolution.
• Cell lineage relationship analysis: Aids in elucidating interrelationships among cell lineages based on Hi-C matrix similarity.
• Chromatin interaction studies: Supports genome-wide analyses of chromatin architecture through reproducibility and comparison metrics.

Methodology:

Computes the stratum adjusted correlation coefficient (SCC) between Hi-C interaction/contact matrices by adjusting for spatial features such as domain structures and distance-dependent interactions.