Polygraph

Polygraph evaluates synthetic regulatory DNA elements based on diversity, motif and k-mer composition, similarity to endogenous sequences, and screening with predictive and foundational models.

Key Features:

• Diversity assessment: Measures sequence diversity within sets of synthetic regulatory elements.
• Motif composition analysis: Evaluates the presence and distribution of regulatory motifs in synthetic DNA sequences.
• k-mer composition analysis: Assesses k-mer frequencies as a feature of synthetic regulatory elements.
• Endogenous similarity scoring: Quantifies similarity between synthetic sequences and endogenous regulatory sequences.
• Predictive model screening: Screens synthetic elements using predictive models.
• Foundational model screening: Screens synthetic elements using foundational models.

Scientific Applications:

• Gene therapy design: Facilitates the design of DNA sequences engineered to drive elevated and cell-type specific expression for therapeutic applications.
• Cell therapy design: Supports the development of regulatory elements for cell-based therapeutic interventions.
• Gene regulatory mechanism research: Improves understanding of gene regulatory mechanisms through systematic sequence assessment.

Methodology:

Polygraph is implemented as a Python framework that systematically evaluates synthetic DNA elements using metrics for diversity, motif and k-mer composition, and similarity to endogenous sequences, combined with screening using predictive and foundational models.