BaitBench: a comprehensive tool for building, as-sessing, and predicting outcomes for hybrid capture enrichment probes

Abstract

The effectiveness of hybridization capture sequencing, a powerful lab technique to isolate and characterize low-abundance samples from complex nucleic acid mixtures, relies heavily on creating a robust probe set. There are a variety of tools that design, evaluate, or simulate capture probes, however, these tools are often siloed and frequently difficult to use. To our knowledge there is no tool that connects all steps of the hybridization capture probe development and analysis process. Here we introduce BaitBench, a comprehensive tool to aid in the design, assessment, and simulation of target capture probes. BaitBench wraps or reimplements in Rust several current tools, and implements a thermodynamic model for simulating capture. Integrating steps allows us to track simulated reads through the whole process enabling us to report sources of false positives and reasons for false negatives. Easy to read output files and the ability to run via command line or GUI interfaces increases usability. We validated BaitBench against publicly available data and achieved a high correlation ({rho} = 0.916), demonstrating its accuracy and translation to real-world settings. Code is available at github.com/niel-infante/BaitBench, with installers for Mac and Windows available at github.com/niel-infante/BaitBench/releases.