Phyloseq is an R package for microbiome analysis that incorporates several data types.
Occassionally our colleagues share a phyloseq object with as an .rds file (R Data Serialization format). It is quite simple to convert that for use in other languages (e.g. python or even Excel!)
Converting the data to .tsv format
This approach requires an R installation somewhere, but we don’t need many commands, so you can probably use a remote R installation on a server!
If you have not yet installed phyloseq, you can do so with bioconductor:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("phyloseq")
Next, we load the phyloseq package and read the .RDS file:
library("phyloseq");
packageVersion("phyloseq"); # check the version we are using
# you may need to use setwd("C:/Users/username/Downloads") to move to whereever you downloaded the file!
p <- readRDS("phyloseq.rds"); # change the filename here!
print(p)
This will print typical output from a phyloseq object like:
phyloseq-class experiment-level object
otu_table() OTU Table: [ 3210 taxa and 11 samples ]
sample_data() Sample Data: [ 11 samples by 12 sample variables ]
tax_table() Taxonomy Table: [ 3210 taxa by 7 taxonomic ranks ]
These are our base phyloseq objects, and we can explore them:
print(otu_table(p))
print(sample_data(p))
And we can also write them to tab separated text in a .tsv file:
write.table(otu_table(p), "p_otu.tsv", sep="\t")
write.table(sample_data(p), "p_sample.tsv", sep="\t")
write.table(tax_table(p), "p_tax.tsv", sep="\t")
Read those files into Python
You can now use pandas to read those files into Python:
import pandas as pd
otu = pd.read_csv("p_otu.tsv", sep="\t")
otu
# sometimes the sample metadata has characters that can't be read using `utf-8` so we have to use `latin-1`
samples = pd.read_csv("p_sample.tsv", sep="\t", encoding='latin-1')
samples
tax = pd.read_csv("p_tax.tsv", sep="\t")
tax
