Polygraph: A Software Framework for the Systematic Assessment of Synthetic Regulatory DNA Elements
Authors/Creators
- 1. College of Computing, Georgia Institute of Technology
- 2. Department of Biology Research | AI Development, Genentech Research and Early Development
Description
The design of regulatory elements is pivotal in numerous therapeutic interventions, including gene and cell therapy, wherein the typical objective is to engineer DNA sequences exhibiting specific attributes like cell-type specificity and elevated expression levels. However, the systematic assessment of these constructed DNA sequences remains challenging due to the absence of robust metrics and an integrated software framework. Here, we introduce Polygraph, a Python framework for evaluating synthetic DNA sequences. Polygraph provides a variety of features to streamline the synthesis and scrutiny of regulatory elements, incorporating features like a diversity index, motif and k-mer composition, similarity to endogenous regulatory sequences, and screening with predictive and foundational models. Consequently, Polygraph stands as a formidable instrument for the assessment of synthetic regulatory sequences, enabling expedited progress in therapeutic applications and enhancing our comprehension of gene regulatory mechanisms.
Code can be found at the following repository: github.com/Genentech/polygraph
Files
human_seqs.txt
Files
(363.3 MB)
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