GBS-DP: a bioinformatics pipeline for processing data coming from genotyping by sequencing

Area of Science:

• Genomics
• Bioinformatics
• Plant Science

Background:

• Next-generation sequencing (NGS) advances plant genotyping.
• Genotyping by sequencing (GBS) offers cost-effective genetic variability identification.
• Existing GBS bioinformatics pipelines often lack automation and flexibility.

Purpose of the Study:

• To develop an automated and versatile bioinformatics pipeline for Genotyping by Sequencing (GBS) data analysis.
• To address limitations in current GBS analysis tools, such as manual processing and software installation challenges.

Main Methods:

• Developed the GBS-DP bioinformatics pipeline using the Snakemake workflow engine.
• Implemented features for full process automation, including software package installation.
• Designed the pipeline for broad applicability across various plant species and large sample sizes.

Main Results:

• The GBS-DP pipeline automates GBS data analysis, enhancing efficiency.
• It supports the analysis of large datasets, accommodating over 400 samples.
• The pipeline is adaptable for diverse plant species.

Conclusions:

• The GBS-DP pipeline provides an efficient, automated solution for GBS data analysis.
• Its flexibility and scalability make it suitable for various plant research applications.
• This tool facilitates rapid genetic variability studies in plants.