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CNPS.cycle: streamlining shotgun metagenomic data analysis for biogeochemical cycles
Zhengfu Yue1,2, Jing Zhang3, Wei Xu1,2
1Key Laboratory of Low-carbon Green Agriculture in Tropical region of China, Ministry of Agriculture and Rural Affairs, Hainan Key Laboratory of Tropical Eco-Circular Agriculture, Environmental and Plant Protection Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou, China.
A new R package, CNPS.cycle, simplifies shotgun metagenomic analysis for environmental biogeochemical cycles. It automates gene and microbe identification, aiding soil ecosystem research.
Area of Science:
- Environmental microbiology
- Computational biology
- Biogeochemistry
Background:
- Shotgun metagenomic data analysis for biogeochemical cycles is complex and resource-intensive.
- Existing methods present barriers for many researchers due to steep learning curves and computational demands.
Purpose of the Study:
- To introduce CNPS.cycle, an R package designed to streamline shotgun metagenomic data interpretation for biogeochemical processes.
- To automate the analysis of carbon, nitrogen, phosphorus, and sulfur cycling.
Main Methods:
- The CNPS.cycle package automates data preprocessing, curation, and differential analysis of microbial genes involved in biogeochemical cycles.
- It includes contig-level microbial analysis, beta-diversity analysis, and data visualization.
- Utilizes annotation files from KEGG and NCBI NR databases.
Main Results:
- CNPS.cycle reveals differentially abundant genes and key microbial players in carbon, nitrogen, phosphorus, and sulfur cycling.
- Provides high-quality tables and images for comprehensive analysis and interpretation.
- Facilitates insights into soil microbial communities and their role in elemental cycles.
Conclusions:
- CNPS.cycle significantly lowers barriers to analyzing complex metagenomic data for biogeochemical research.
- The package enhances understanding of soil ecosystems and microbial contributions to elemental cycling.
- Offers accessible, automated analysis for environmental scientists and researchers.
