Community-level chemical metrics for exploring genomic adaptation to environments (2023)

This vignette was compiled on 2024-03-11 with JMDplots 1.2.19-11 and chem16S 1.0.0-16.

Code example and plots (Figure 1)

chem16S_1()

## [1] "map_taxa: mapping rate to GTDB taxonomy is 100.0%"
## [1] "map_taxa: using these manual mapping(s) to NCBI RefSeq:"
## [1] "map_taxa: can't map groups order_Stramenopiles (12.94%), family_ACK-M1 (3.27%), 374 others (11.75%)"
## [1] "map_taxa: mapping rate to RefSeq taxonomy is 71.9%"

Data sources: The GlobalPatterns dataset is from the phyloseq package (McMurdie and Holmes, 2013) and is adapted from Caporaso et al. (2011). The mouse gut dataset was created by analyzing sequence data from Schloss et al. (2012) (downloaded here and used in the mothur MiSeq SOP and DADA2 Pipeline Tutorial) with the DADA2 pipeline modified to use the GTDB training set (Alishum, 2022) for taxonomic classifications.

References

Alishum A. 2022. DADA2 formatted 16S rRNA gene sequences for both bacteria & archaea. Zenodo. doi: 10.5281/zenodo.6655692

Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Lozupone CA, Turnbaugh PJ, Fierer N, Knight R. 2011. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proceedings of the National Academy of Sciences 108(Supplement 1): 4516–4522. doi: 10.1073/pnas.1000080107

McMurdie PJ, Holmes S. 2013. phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. PLOS One 8(4): e61217. doi: 10.1371/journal.pone.0061217

Schloss PD, Schubert AM, Zackular JP, Iverson KD, Young VB, Petrosino JF. 2012. Stabilization of the murine gut microbiome following weaning. Gut Microbes 3(4): 383–393. doi: 10.4161/gmic.21008

JMDplots vignettes

Community-level chemical metrics for exploring genomic adaptation to environments (2023)

Code example and plots (Figure 1)

References