GLANET

GLANET annotates and performs enrichment analysis of genomic loci from next-generation sequencing (NGS) datasets to interpret genetic variations, transcription factor (TF) occupancy, and histone modifications against genomic and epigenomic annotations.

Key Features:

• Sampling-Based Enrichment Test: Implements a sampling-based enrichment test that accounts for GC content and mappability, either jointly or separately, to control Type-I error and maintain statistical power.
• Extensive Annotation Library: Evaluates loci against a repository of genomic and epigenomic annotations and can be extended with user-supplied gene sets and genomic intervals.
• Impact Assessment of SNPs on TF Binding: Assesses the impact of single nucleotide polymorphisms (SNPs) on transcription factor (TF) binding sites.
• Regulation-Based Pathway Enrichment Analysis: Performs regulation-based pathway enrichment analysis to link loci to biological pathways and regulatory networks.
• Power and Type-I Error Evaluation: Employs a data-driven computational approach to assess the power and Type-I error of its enrichment procedures.

Scientific Applications:

• Annotation and Interpretation of NGS Loci: Interpretation of genomic loci derived from NGS that represent genetic variation, TF occupancy, or histone modifications using genomic and epigenomic annotations.
• Regulatory Variant Analysis: Prioritization and functional interpretation of SNPs that may alter TF binding and regulatory activity.
• Pathway and Network Inference: Identification of enriched biological pathways and regulatory networks associated with genomic loci.
• Gene Regulation and Disease Mechanisms: Linking genomic and epigenomic loci to gene regulation, disease mechanisms, and potential therapeutic targets.

Methodology:

Evaluating loci against a genomic and epigenomic annotation repository; sampling-based enrichment testing that controls for GC content and mappability (jointly or separately); regulation-based pathway enrichment analysis; SNP impact assessment on TF binding sites; and a data-driven computational evaluation of power and Type-I error.