iTAR

iTAR identifies target genes of transcription factors from ChIP-seq or ChIP-chip data to support analysis of transcriptional regulatory interactions.

Key Features:

• Gaussian mixture model p-value estimation: Implements a Gaussian mixture model for p-value estimation to increase sensitivity and better capture TF binding profile distributions.
• Binding-peak identification and quantification: Identifies and quantifies locations and strengths of TF binding peaks within significant promoter regions of target genes.
• Flexible input formats: Supports multiple input file formats and genome assembly versions for ChIP-seq and ChIP-chip datasets.
• Cross-species compatibility: Supports target gene identification across seven species ranging from yeast to human.
• GO enrichment analysis: Performs Gene Ontology (GO) enrichment analysis on identified target genes to link targets to functions and pathways.
• Quality assessment visualizations: Generates characteristic binding profile charts and density plots of normalized regulatory scores to assess data quality and signal distribution.

Scientific Applications:

• Transcriptional regulation: Identifying TF–target gene relationships to study transcriptional regulatory mechanisms.
• Comparative and evolutionary genomics: Enabling cross-species comparisons of TF target sets from yeast to human.
• Functional genomics: Linking identified targets to biological processes and pathways via GO enrichment analysis.

Methodology:

Analyzes ChIP-seq or ChIP-chip data using a probabilistic approach that estimates significance with a Gaussian mixture model, integrates binding-peak data by identifying and quantifying peaks within promoter regions, performs GO enrichment analysis on identified targets, and generates binding profile charts and density plots of normalized regulatory scores.