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Detecting Foldback Artifacts in Long-reads

2025/07/18 by Jakob Heinz, Matthew Meyerson, Heng Li · 1 voice · 1 citation
Computer Science · #Natural Language Processing Techniques #Topic Modeling #Handwritten Text Recognition Techniques

paper · doi:10.1101/2025.07.15.664946

openalex publication_date 2025/07/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01

Abstract

Long-read sequencing data is useful for detecting large and complex structural variations; however, technical artifacts can lead to false structural variant calls. In our analyses, we became aware of a foldback artifact in long-read data. Therefore, we developed the open-source Breakinator tool to flag putative foldback artifact reads, as well as previously known chimeric artifacts. Through an alignment-based approach, Breakinator can detect artifacts missed by existing quality control tools. We profiled the occurrences of foldbacks and chimeric reads in both Oxford Nanopore and PacBio sequences across a range of specimens, library types, sequencing chemistries, sequencing machines, and base-calling software.

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