OLOGRAM

OLOGRAM assesses the statistical significance of total overlap length between sets of genomic regions to evaluate their functional relationships.

Key Features:

• Total overlap length focus: Computes and tests significance of the cumulative length of overlaps between genomic region sets.
• Overlap statistics: Performs detailed statistics on overlaps between regions provided in BED or GTF formats.
• Monte Carlo simulation: Uses Monte Carlo shuffling to model the distribution of overlap lengths while accounting for region and inter-region length distributions.
• Negative binomial model: Fits a negative binomial model to total overlap length to obtain p-values for overlap significance.
• User-defined exclusions: Supports exclusion of user-specified genomic areas during shuffling.

Scientific Applications:

• Functional relationship analysis: Evaluates whether two sets of genomic coordinates are functionally associated based on overlap length.
• Gene regulation studies: Tests significance of overlaps between regulatory elements and genes or transcripts.
• Chromatin interaction analysis: Assesses overlap-based evidence for chromatin contacts or domains.
• Genomic feature enrichment: Quantifies and statistically tests enrichment of overlaps between diverse genomic features.

Methodology:

Accepts BED or GTF inputs; performs Monte Carlo shuffling that accounts for region and inter-region length distributions to generate overlap length distributions; fits a negative binomial model to the total overlap length to derive p-values; supports exclusion regions during shuffling.