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sangerFlow, an Automated Bioinformatics Pipeline to Analyze Sanger Amplicon Sequencing Data for Pest and Pathogen Diagnosis
Journal article   Open access   Peer reviewed

sangerFlow, an Automated Bioinformatics Pipeline to Analyze Sanger Amplicon Sequencing Data for Pest and Pathogen Diagnosis

M. Asaduzzaman Prodhan, Matthew Power and Monica Kehoe
PhytoFrontiers, Vol.5(3), pp.295-299
2025
DOI: https://doi.org/10.1094/PHYTOFR-09-24-0104-SC
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CC BY-NC-ND V4.0,  Open Access

Abstract

Polymerase chain reaction (PCR) amplicon sequencing allows for reliable identification of an organism by amplifying and analyzing a single conserved marker gene or DNA barcode. As this approach generally involves a single gene, it is an easier protocol to run compared with multilocus or whole-genome sequencing for diagnostic purposes, yet considerably reliable. Therefore, Sanger-based high-quality amplicon sequencing is widely deployed for species identification and high-throughput biosecurity surveillance. However, keeping up with the data analysis in large-scale surveillance or diagnostic settings could be a limiting factor because it involves manual quality control of the raw sequencing data, alignment of the forward and reverse reads, and, finally, a web-based Blastn search of all the amplicons. Here, we present a bioinformatics pipeline that automates the entire analysis. As a result, the pipeline is scalable with a high volume of samples and reproducible. Furthermore, the pipeline leverages the modern open-source Nextflow and Singularity concept; thus, it does not require software installation, except for Nextflow and Singularity, or any paid commercial software or programming expertise from the end users, making it widely adaptable. [Formula: see text]

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