TreeGibbsSampler

TreeGibbsSampler identifies sequence motifs by integrating motif overrepresentation with evolutionary conservation across multiple genomes, including closely and distantly related species, without requiring pre-aligned orthologous sequences.

Key Features:

• Integration of overrepresentation and conservation: Combines motif overrepresentation analysis with evolutionary conservation to prioritize motifs that are both statistically enriched and conserved across species.
• Independence from pre-aligned orthologous sequences: Operates without requiring pre-aligned orthologous sequences, enabling analysis across distant species where alignments are unreliable.
• Extraction of regulatory elements: Identifies candidate regulatory sequences, including transcription factor binding sites and enhancers, by focusing on conserved and overrepresented motifs.
• Phylogeny-aware analysis: Incorporates phylogenetic relationships among input sequences to assess motif conservation across tree branches.

Scientific Applications:

• Comparative genomics: Detects conserved regulatory motifs across species to support cross-species regulatory element annotation.
• Evolutionary biology: Infers motifs under evolutionary constraint by assessing conservation across phylogenetic trees.
• Functional genomics: Identifies candidate transcription factor binding sites and enhancers for downstream experimental validation.

Methodology:

Constructs a phylogenetic tree from sequence data and applies Gibbs sampling to identify motifs that are both overrepresented in the dataset and conserved across the branches of the tree.