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Comparative Evaluation of Open-Source Bioinformatics Pipelines for Full-Length Viral Genome Assembly.
Levente Zsichla1,2, Marius Zeeb3,4, Dávid Fazekas1,5
1Institute of Biology, ELTE Eötvös Loránd University, 1117 Budapest, Hungary.
Viruses
|January 8, 2025
Summary
Choosing bioinformatics pipelines for viral genome assembly from next-generation sequencing (NGS) data is crucial. Shiver and SmaltAlign offer robust performance for divergent samples, ensuring accurate viral genome reconstruction.
Area of Science:
- Bioinformatics and Computational Biology
- Genomics and Genetics
- Virology and Infectious Diseases
Background:
- Next-generation sequencing (NGS) is increasingly used in clinical diagnostics and epidemiology.
- This necessitates efficient, automated, and user-friendly bioinformatics workflows for viral genome assembly.
- Evaluating existing tools is essential to guide researchers in selecting appropriate pipelines.
Purpose of the Study:
- To assess the performance and applicability of four open-source bioinformatics pipelines for full-length viral genome assembly from NGS data.
- To compare pipelines using simulated and real-world HIV-1 datasets.
- To provide recommendations for pipeline selection based on data characteristics and user needs.
Main Methods:
- Evaluated four pipelines: shiver (including a Dockerized version, dshiver), SmaltAlign, viral-ngs, and V-pipe.
- Utilized simulated and real-world HIV-1 paired-end short-read datasets with default settings.
- Assessed performance based on quality metrics (genome fraction recovery, mismatch/indel rates, variant calling F1 scores), runtime, and user-friendliness.
Main Results:
- All pipelines achieved high-quality consensus genome assemblies with highly similar reference sequences.
- Shiver and SmaltAlign demonstrated robust performance with more divergent samples (non-matching subtypes).
- SmaltAlign and viral-ngs had significantly shorter runtimes on empirical datasets compared to V-Pipe and shiver; V-Pipe offered the broadest functionalities, SmaltAlign and dshiver balanced user-friendliness with robustness, and viral-ngs required fewer computational resources.
Conclusions:
- For closely matched reference sequences, all evaluated pipelines reliably reconstruct viral consensus genomes.
- Pipeline choice can be guided by user-friendliness and runtime considerations.
- For divergent samples lacking a matched reference, shiver or SmaltAlign are recommended for robust performance; dshiver enhances shiver's usability.
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