SUMMARY: Duplex-Indel is a novel Snakemake workflow for detecting somatic small insertions and deletions (Indels) from Tn5 transposase-based duplex sequencing data. Duplex-Indel enhances the accuracy of mutation calling at the single-molecule level by requiring consensus support from both DNA strands for each somatic Indel, minimizing confounding from technical artifacts. Duplex-Indel extends somatic mutation calling in Tn5 transposase-based duplex sequencing data to include Indels. We have demonstrated the accuracy and robustness of Duplex-Indel using cancer cell lines. AVAILABILITY AND IMPLEMENTATION: Source code and documentation are available under the MIT license on GitHub at https://github.com/ealee-lab/duplex-indel and archived on Zenodo at https://doi.org/10.5281/zenodo.19228799.

Hi-C is a common technique for assessing 3D chromatin conformation. Recent studies have shown that long-range interaction information in Hi-C data can be used to generate chromosome-length genome assemblies and identify large-scale structural variations. Here, we demonstrate the use of Hi-C data in detecting mobile transposable element (TE) insertions genome-wide. Our pipeline Hi-C-based TE analyzer (HiTea) capitalizes on clipped Hi-C reads and is aided by a high proportion of discordant read pairs in Hi-C data to detect insertions of three major families of active human TEs. Despite the uneven genome coverage in Hi-C data, HiTea is competitive with the existing callers based on whole-genome sequencing (WGS) data and can supplement the WGS-based characterization of the TE-insertion landscape. We employ the pipeline to identify TE-insertions from human cell-line Hi-C samples. AVAILABILITY AND IMPLEMENTATION: HiTea is available at https://github.com/parklab/HiTea and as a Docker image. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.