The microbiome package has import functions for certain standard data formats for 16S profiling (Simple CSV, Mothur, biom). For details, see the function help. To import these, use:
# Import output CSV files generated by write_phyloseq
pseq1 <- read_phyloseq(otu.file, taxonomy.file, metadata.file, type = "simple")
# Import mother .shared and .taxonomy and metadata files
pseq2 <- read_phyloseq(otu.file, taxonomy.file, metadata.file, type = "mothur")
# Import BIOM files
pseq3 <- read_phyloseq(otu.file, taxonomy.file, metadata.file, type = "biom")
You can also use additional import functions from the independent phyloseq R package.
Alternatively, you can read your data in R (read.table, read.csv or other standard functions) and convert into phyloseq format. The procedure is well explained in the phyloseq tutorial from the independent phyloseq R package. See also examples on manipulating for phyloseq objects.
The HITChip Atlas data set is available via the microbiome R package in phyloseq format, and via Data Dryad in tabular format. This data set from Lahti et al. Nat. Comm. 5:4344, 2014 comes with 130 genus-like taxonomic groups across 1006 western adults with no reported health complications. Some subjects have also short time series. Load the data in R with:
# Data citation doi: 10.1038/ncomms5344
library(microbiome)
data(atlas1006)
print(atlas1006)
## phyloseq-class experiment-level object
## otu_table() OTU Table: [ 130 taxa and 1151 samples ]
## sample_data() Sample Data: [ 1151 samples by 10 sample variables ]
## tax_table() Taxonomy Table: [ 130 taxa by 3 taxonomic ranks ]
A two-week diet swap study between western (USA) and traditional (rural Africa) diets, reported in O’Keefe et al. Nat. Comm. 6:6342, 2015. The data is also available for download from Data Dryad. Load in R with:
# Data citation doi: 10.1038/ncomms7342
data(dietswap)
print(dietswap)
## phyloseq-class experiment-level object
## otu_table() OTU Table: [ 130 taxa and 222 samples ]
## sample_data() Sample Data: [ 222 samples by 8 sample variables ]
## tax_table() Taxonomy Table: [ 130 taxa by 3 taxonomic ranks ]
Data set from Lahti et al. PeerJ 1:e32, 2013 characterizes associations between human intestinal microbiota and blood serum lipids. Note that this data set contains an additional data matrix of lipid species. Load the data in R with:
# Data citation doi: 10.7717/peerj.32
data(peerj32)
print(names(peerj32))
## [1] "lipids" "microbes" "meta" "phyloseq"