cisRED

cisRED identifies and ranks conserved regulatory elements genome-wide by predicting and scoring motifs in promoter regions using comparative sequence sets that include corresponding vertebrate sequences.

Key Features:

• Genome-scale identification: Identifies conserved regulatory elements across diverse target genomes at genome scale.
• Multiple discovery methods: Integrates multiple motif discovery and post-processing methods for prediction and ranking.
• Promoter-region focus: Predicts motifs specifically within promoter regions using corresponding sequences from vertebrates.
• High-throughput pipeline: Employs a high-throughput pipeline that applies discovery and post-processing methods to target sequences.
• Adaptive randomized controls: Applies randomized sequence sets derived adaptively from the original target sequences as controls.
• Statistical significance estimation: Calculates p-values to estimate motif significance and retains motifs below a predefined threshold.
• Motif grouping and co-occurrence: Identifies groups of similar motifs and detects co-occurring motif patterns to characterize regulatory organization.
• Structured motif database: Stores information on atomic motifs, motif groups, and motif patterns for downstream analysis.

Scientific Applications:

• Gene regulation studies: Enables identification and analysis of putative regulatory elements controlling gene expression.
• Comparative genomics: Facilitates cross-species comparison of conserved motifs using vertebrate sequence sets.
• Evolutionary biology: Supports investigation of conservation and divergence of regulatory elements across genomes.
• Motif characterization: Assists in delineating motif families and co-occurrence patterns relevant to regulatory logic.

Methodology:

Applies various computational motif discovery and post-processing methods in a high-throughput pipeline, uses adaptively derived randomized sequence sets to calculate p-values for motif significance, and groups similar motifs and co-occurring patterns.