Snapshot of analysis code for Umi-pipeline-nf: A modular and scalable workflow for UMI-tagged nanopore amplicon analysis with real time sequencing integration and GPU-acceleration

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Authors: Stephan Amstler, Lukas Forer, Lara Escherich, Sebastian Schoenherr, Coassin Stefan
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Abstract

This record contains a frozen snapshot of the analysis code associated with the manuscript: “Umi-pipeline-nf: A modular and scalable workflow for UMI-tagged nanopore amplicon analysis with real-time sequencing integration and GPU-acceleration.” The repository provides the complete, versioned source code required to reproduce the analyses described in the publication and the experiments of the revision. The workflow is implemented using Nextflow and is designed for scalable, reproducible processing of UMI-tagged Oxford Nanopore amplicon sequencing data. The Workflow is freely available on GitHub. Contents of this record umi-pipeline-nf-1.0.1.tar.gzStable release of the workflow corresponding to the manuscript. umi-pipeline-nf_Paper-1.0.0.tar.gzAn exact snapshot of the pipeline used for the analyses in the paper. UMI_simulator.tar.gzSimulator used for generating synthetic UMI datasets for benchmarking experiments for the Revision. Usage The pipeline is executed using Nextflow. Detailed installation and usage instructions are provided in the repository README on GitHub. Version This Zenodo record corresponds to version 1.0.1 of umi-pipeline nf and version 1.0.0 of the analysis code to reproduce the results of the manuscript. The UMI simulator is not available on GitHub and has no version assigned. Source code repository The actively maintained source code of the pipeline is available at: https://github.com/genepi/umi-pipeline-nf License This software is distributed under the Mozilla Public License Version 2.0 (MPL 2.0) license. If you use this workflow, please cite the associated publication (and this Zenodo record).

Fields of Study & Subjects

Genomics and Phylogenetic Studies Scientific Computing and Data Management Single-cell and spatial transcriptomics

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
11 February 2026
Language
EN