microeco: an R package for data mining in microbial community ecology

ABSTRACT A large amount of sequencing data is produced in microbial community ecology studies using the high-throughput sequencing technique, especially amplicon-sequencing-based community data. After conducting the initial bioinformatic analysis of amplicon sequencing data, performing the subsequen...

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Veröffentlicht in:FEMS microbiology ecology 2021-02, Vol.97 (2), p.1
Hauptverfasser: Liu, Chi, Cui, Yaoming, Li, Xiangzhen, Yao, Minjie
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Sprache:eng
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Zusammenfassung:ABSTRACT A large amount of sequencing data is produced in microbial community ecology studies using the high-throughput sequencing technique, especially amplicon-sequencing-based community data. After conducting the initial bioinformatic analysis of amplicon sequencing data, performing the subsequent statistics and data mining based on the operational taxonomic unit and taxonomic assignment tables is still complicated and time-consuming. To address this problem, we present an integrated R package-‘microeco’ as an analysis pipeline for treating microbial community and environmental data. This package was developed based on the R6 class system and combines a series of commonly used and advanced approaches in microbial community ecology research. The package includes classes for data preprocessing, taxa abundance plotting, venn diagram, alpha diversity analysis, beta diversity analysis, differential abundance test and indicator taxon analysis, environmental data analysis, null model analysis, network analysis and functional analysis. Each class is designed to provide a set of approaches that can be easily accessible to users. Compared with other R packages in the microbial ecology field, the microeco package is fast, flexible and modularized to use and provides powerful and convenient tools for researchers. The microeco package can be installed from CRAN (The Comprehensive R Archive Network) or github (https://github.com/ChiLiubio/microeco). An integrated and powerful R package-microeco was developed for researchers to perform data mining of amplicon sequencing in microbial community ecology.
ISSN:1574-6941
0168-6496
1574-6941
DOI:10.1093/femsec/fiaa255