Bioconductor workflow for microbiome data analysis: from raw reads to community analyses
Indexed incrossrefdoaj
Abstract
High-throughput sequencing of PCR-amplified taxonomic markers (like the 16S rRNA gene) has enabled a new level of analysis of complex bacterial communities known as microbiomes. Many tools exist to quantify and compare abundance levels or microbial composition of communities in different conditions. The sequencing reads have to be denoised and assigned to the closest taxa from a reference database. Common approaches use a notion of 97% similarity and normalize the data by subsampling to equalize library sizes. In this paper, we show that statistical models allow more accurate abundance estimates. By providing a complete workflow in R, we enable the user to do sophisticated downstream statistical analyses,…
Citation impact
738
total citations
- FWCI
- 18.28
- Percentile
- 100%
- References
- 35
Citations per year
Authors
5Topics & keywords
Topics
Keywords
- Bioconductor
- Microbiome
- Workflow
- Nonparametric statistics
- Computer science
- Metagenomics
- Data mining
- Computational biology
UN Sustainable Development Goals
- Life in Land
No related works found for this paper.