SQMtools: automated processing and visual analysis of 'omics data with R and anvi'o

Area of Science:

• Environmental microbiology
• Metagenomics
• Bioinformatics

Background:

• High-throughput sequencing costs have decreased, increasing its use in microbial community analysis.
• Non-specialists face challenges in selecting analysis methods and interpreting large datasets.
• Environmental microbial community analysis requires accessible bioinformatics tools.

Purpose of the Study:

• To present an automated workflow for processing raw sequencing data.
• To simplify the analysis of environmental microbial communities for non-expert users.
• To integrate SqueezeMeta and anvi'o for seamless data exploration.

Main Methods:

• Utilized SqueezeMeta for automated read processing, contig annotation, and genome binning.
• Developed custom scripts for integrating SqueezeMeta output into the anvi'o platform.
• Created an R package for enhanced data visualization and analysis.

Main Results:

• Successfully automated the processing of raw sequencing reads into annotated contigs and reconstructed genomes.
• Enabled filtering and visual exploration of analysis results within the anvi'o platform.
• Provided a user-friendly interface for R users to access SqueezeMeta results.

Conclusions:

• The workflow empowers non-expert users to transition from raw sequencing reads to insightful custom plots.
• It offers a powerful, flexible, and well-documented solution for microbial community analysis.
• Simplifies complex bioinformatics pipelines for broader accessibility.