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Updated: Aug 6, 2026

Targeted DNA Methylation Analysis by Next-generation Sequencing
Published on: February 24, 2015
ALPINE: a scalable pipeline for comprehensive classification of gene-editing outcomes from long-read amplicon
Yu Chen1, Xing-Huang Gao2, Athea Vichas2
1Research and Development, Bristol-Myers Squibb Company, Princeton, NJ 08540, United States.
Summary:
CRISPR genome editing has enabled precise genetic modification for gene and cell therapies, but edits often produce heterogeneous on-target outcomes, including homology-directed repair (HDR) knock-ins, DNA repair template integrations, and structural variants. Existing tools are frequently limited to short reads or lack viral vector-specific integration categories needed for therapeutic development. Here, we present ALPINE (Amplicon Long-read Pipeline for INtegration Evaluation), a scalable and reproducible pipeline for classifying and quantifying gene-editing outcomes from long-read amplicon sequencing supporting both PacBio HiFi and Oxford Nanopore platforms. ALPINE classifies reads into 10+ categories, including DNA repair vector integration subtypes, and performs variant calling near the gene-edited site with batch, multi-sample reporting. Uniquely, ALPINE can distinguish between cells treated with multiple DNA repair vectors and identify distinct molecular features, such as inverted terminal repeats (ITRs), enabling comprehensive characterization of complex gene editing outcomes. Dual-target benchmarking on simulated datasets demonstrated high accuracy for transgene integration events. Independent validation on public crosslinked-HDR dataset confirmed ALPINE's integration detection capabilities, and application to edited T cell samples demonstrated comprehensive gene-editing outcome profiling.
Availability:
ALPINE is available under MIT license at https://github.com/Maggi-Chen/ALPINE and https://doi.org/10.5281/zenodo.20272510. All analysis scripts and visualization code used in this manuscript are available at https://github.com/Maggi-Chen/ALPINE-manuscript-analysis. Simulated datasets are deposited at Zenodo (https://doi.org/10.5281/zenodo.20260865). Public dataset PRJNA913199 is available through NCBI SRA.