ProBias

ProBias identifies and quantifies compositionally biased segments (CBS) in protein sequences to support analysis of amino-acid enrichment relevant to molecular function, evolution, and disease.

Key Features:

• User-defined bias detection: Allows specification of amino-acid sets for targeted detection of compositional bias.
• Statistical significance estimation: Applies discrete scan statistics to estimate the statistical significance of detected CBS and implements multiple-testing correction.
• Global compositional bias consideration: Accounts for global (sequence-wide) compositional bias when evaluating local clusters to distinguish local enrichment from background composition effects.
• Sensitivity and precision: Detects subtle deviations from a random-independence background model to identify potentially functional CBS in complex sequences.

Scientific Applications:

• Functional annotation: Highlights candidate regions or domains in uncharacterized proteins based on significant compositional enrichment patterns.
• Disease association studies: Supports linking protein groups and biological processes to characteristic CBS types to inform hypotheses about disease mechanisms.
• Evolutionary analysis: Enables large-scale assessment of CBS conservation across protein families and lineages.

Methodology:

Applies discrete scan statistics to detect CBS, quantifies statistical significance with multiple-testing correction, and incorporates global (sequence-wide) compositional bias when evaluating local enrichment.