ASAP

ASAP detects and evaluates over-represented transcription factor binding sites in promoter sets to support analysis of gene regulatory mechanisms in co-regulated genes.

Key Features:

• Enhanced Suffix Arrays: A fast search engine based on enhanced suffix arrays enables rapid scanning of large genomic datasets for candidate binding sites.
• Position Weight Matrices (PWMs): Support for position weight matrices (PWMs) provides a probabilistic model for detecting specific transcription factor binding motifs in DNA sequences.
• Over-Representation Analysis: Statistical assessment of motif over-representation compares promoter sets derived from co-regulated genes against background sequences to identify significant regulatory elements.
• Statistical Methods: Incorporates standard statistical approaches, including binomial tests and Fisher's exact test, with performance reported as robust across different threshold values and sequence distributions.
• Performance Optimization: Optimized for speed to outperform naive scanning algorithms when processing large datasets with numerous weight matrices.

Scientific Applications:

• Gene regulation analysis: Identification of shared transcription factor binding sites among co-regulated genes to elucidate regulatory mechanisms.
• Disease-associated motif discovery: Linking specific over-represented motifs to pathological conditions to explore genetic bases of disease.
• Evolutionary conservation studies: Investigation of conservation of regulatory sequences and motifs across species.

Methodology:

ASAP scans DNA sequences using enhanced suffix arrays with position weight matrices, applies statistical tests (including binomial tests and Fisher's exact test) to assess motif over-representation in promoters versus background, and supports systematic comparison of these statistical methods with control of input data parameters.