KAS-Analyzer: a novel computational framework for exploring KAS-seq data

MOTIVATION: Kethoxal-assisted ssDNA sequencing (KAS-seq) is rapidly gaining popularity as a robust and effective approach to study the nascent dynamics of transcriptionally engaged RNA polymerases through profiling of genome-wide single-stranded DNA (ssDNA). Its latest variant, spKAS-seq, a strand-specific version of KAS-seq, has been developed to map genome-wide R-loop structures by detecting imbalances of ssDNA on two strands. However, user-friendly, open-source computational tools tailored for KAS-seq data are still lacking. RESULTS: Here, we introduce KAS-Analyzer, the first comprehensive computational framework aimed at streamlining and enhancing the analysis and interpretation of KAS-seq and spKAS-seq data. In addition to standard analyses, KAS-Analyzer offers many novel tools specifically designed for KAS-seq data, including, but not limited to: calculation of transcription-related metrics, identification of single-stranded transcribing (SST) enhancers, high-resolution mapping of R-loops, and differential RNA polymerase activity analysis. We provided a detailed overview of KAS-seq data and its diverse applications through the implementation of KAS-Analyzer. Using the example time-course KAS-seq datasets, we further showcase the robust capabilities of KAS-Analyzer for investigating dynamic transcriptional regulatory programs in response to UVB radiation. AVAILABILITY AND IMPLEMENTATION: KAS-Analyzer is available at https://github.com/Ruitulyu/KAS-Analyzer.