Nothing
## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
warning = FALSE
)
suppressPackageStartupMessages(library(metagenomeFeatures))
suppressPackageStartupMessages(library(phyloseq))
## ----message = FALSE----------------------------------------------------------
library(metagenomeFeatures)
gg85 <- get_gg13.8_85MgDb()
## -----------------------------------------------------------------------------
data(qiita_study_94_gg_ids)
## -----------------------------------------------------------------------------
soil_mgF <- annotateFeatures(gg85, qiita_study_94_gg_ids)
## Taxonomic heirarchy
soil_mgF
# Sequence data
mgF_seq(soil_mgF)
# Tree data
mgF_tree(soil_mgF)
## -----------------------------------------------------------------------------
data_dir <- system.file("extdata", package = "metagenomeFeatures")
## Load Biom
biom_file <- file.path(data_dir, "229_otu_table.biom")
soil_ps <- phyloseq::import_biom(BIOMfilename = biom_file)
## Define sample data
sample_file <- file.path(data_dir, "229_sample_data.tsv")
sample_dat <- read.delim(sample_file)
## Rownames matching sample_names(), required for phyloseq sample_data slot
rownames(sample_dat) <- sample_dat$SampleID
sample_data(soil_ps) <- sample_dat
## Resulting phyloseq object
soil_ps
## -----------------------------------------------------------------------------
# Removing OTUs not in `gg85`
soil_tree <- mgF_tree(soil_mgF)
soil_ps_gg85 <- prune_taxa(taxa = soil_tree$tip.label, x = soil_ps)
# Removing samples with no OTUs in `gg85`
samples_to_keep <- sample_sums(soil_ps_gg85) != 0
soil_ps_gg85 <- prune_samples(samples = samples_to_keep, x = soil_ps_gg85)
## -----------------------------------------------------------------------------
## Defining tree slot
phy_tree(physeq = soil_ps_gg85) <- soil_tree
## Defining seq slot
soil_ps_gg85@refseq <- mgF_seq(soil_mgF)
## ----betaFig, fig.cap="Beta diversity and ordination for a subset of features from Rousk et al. [-@rousk2010soil]. Beta diversity was estimated using Weighted Unifrac and Principal Component Analysis was used for ordination. Sampels are represented as individual point and color indicates soil sample pH."----
soil_ord <- ordinate(physeq = soil_ps_gg85,
distance = "wunifrac",
method = "PCoA")
plot_ordination(soil_ps_gg85, soil_ord,
color = "ph",
type="sample",
label = "SampleID")
## ----sessionInfo, echo=FALSE--------------------------------------------------
sessionInfo()
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.