BacSeq: A User-Friendly Automated Pipeline for Whole-Genome Sequence Analysis of Bacterial Genomes

Author:

Chukamnerd Arnon1ORCID,Jeenkeawpiam Kongpop2,Chusri Sarunyou1ORCID,Pomwised Rattanaruji3ORCID,Singkhamanan Kamonnut2ORCID,Surachat Komwit245ORCID

Affiliation:

1. Division of Infectious Diseases, Department of Internal Medicine, Faculty of Medicine, Prince of Songkla University, Songkhla 90110, Thailand

2. Department of Biomedical Sciences and Biomedical Engineering, Faculty of Medicine, Prince of Songkla University, Songkhla 90110, Thailand

3. Division of Biological Science, Faculty of Science, Prince of Songkla University, Songkhla 90110, Thailand

4. Translational Medicine Research Center, Faculty of Medicine, Prince of Songkla University, Songkhla 90110, Thailand

5. Division of Computational Science, Faculty of Science, Prince of Songkla University, Songkhla 90110, Thailand

Abstract

Whole-genome sequencing (WGS) of bacterial pathogens is widely conducted in microbiological, medical, and clinical research to explore genetic insights that could impact clinical treatment and molecular epidemiology. However, analyzing WGS data of bacteria can pose challenges for microbiologists, clinicians, and researchers, as it requires the application of several bioinformatics pipelines to extract genetic information from raw data. In this paper, we present BacSeq, an automated bioinformatic pipeline for the analysis of next-generation sequencing data of bacterial genomes. BacSeq enables the assembly, annotation, and identification of crucial genes responsible for multidrug resistance, virulence factors, and plasmids. Additionally, the pipeline integrates comparative analysis among isolates, offering phylogenetic tree analysis and identification of single-nucleotide polymorphisms (SNPs). To facilitate easy analysis in a single step and support the processing of multiple isolates, BacSeq provides a graphical user interface (GUI) based on the JAVA platform. It is designed to cater to users without extensive bioinformatics skills.

Funder

the Faculty of Science, Prince of Songkla University

Publisher

MDPI AG

Subject

Virology,Microbiology (medical),Microbiology

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