Bioconductor Microbiome Workflow Files
Abstract/Contents
- 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 OTU 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 eqalize 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, whether
parametric or non-parametric. We provide examples of using the R
packages dada2, phyloseq, DESeq2 and vegan to filter, visualize and
test microbiome data and community networks.
Description
| Type of resource | software, multimedia |
|---|---|
| Date created | May 30, 2016 |
Creators/Contributors
| Author | Holmes, Susan | |
|---|---|---|
| Author | Callahan, Ben | |
| Author | Sankaran, Kris | |
| Author | Fukuyama, Julia | |
| Author | McMurdie, Paul J |
Subjects
| Subject | microbiome |
|---|---|
| Subject | bioconductor workflow |
| Subject | ordination |
| Subject | 16S rRNA |
| Subject | dada2 |
| Subject | phyloseq |
| Subject | networks |
| Subject | Statistics Department Stanford |
| Genre | Dataset |
Bibliographic information
| Related Publication |
Ben J. Callahan, Kris Sankaran, Julia A. Fukuyama, Paul J. McMurdie, Susan P. Holmes,
|
|---|---|
| Related item |
|
| Location | https://purl.stanford.edu/wh250nn9648 |
Access conditions
- Use and reproduction
- User agrees that, where applicable, content will not be used to identify or to otherwise infringe the privacy or confidentiality rights of individuals. Content distributed via the Stanford Digital Repository may be subject to additional license and use restrictions applied by the depositor.
- License
- This work is licensed under a Creative Commons Attribution Share Alike 3.0 Unported license (CC BY-SA).
Preferred citation
- Preferred Citation
Supplementary Files to:
Ben J. Callahan, Kris Sankaran, Julia A. Fukuyama, Paul J. McMurdie, Susan P. Holmes,
Bioconductor workflow for microbiome data analysis: from raw reads to community analyses,
F1000Research 2016, 5:1492 (doi: 10.12688/f1000research.8986.1).
Collection
Reproducible Research Support for Statistics of the Microbiome
View other items in this collection in SearchWorksContact information
- Contact
- susan@stat.stanford.edu
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