Probe summarization

Summarize (preprocessed) oligo-level data into phylotype level; examples with simulated data; see read_hitchip to use your own data. We use and recommend the Robust Probabilistic Averaging (RPA) for probe summarization.

library(microbiome)

library(HITChipDB)
data.directory <- system.file("extdata", package = "microbiome")

# Read oligo-level data (here: simulated example data)
probedata <- HITChipDB::read_hitchip(data.directory, method = "frpa")$probedata

# Read phylogeny map
# NOTE: use phylogeny.filtered for species/L1/L2 summarization
# Load taxonomy from output directory
f <- system.file("inst/extdata/get_hitchip_taxonomy.R", package = "microbiome")
source(f)
taxonomy <- get_hitchip_taxonomy("HITChip", "filtered")

# Summarize oligos into higher level phylotypes
dat <- RPA::summarize_probedata(
                 probedata = probedata,
         taxonomy = taxonomy, 
                 method = "rpa",
         level = "species")

Retrieve probe-level data

Get probes for each probeset:

sets <- RPA::retrieve.probesets(taxonomy, level = "species", name = NULL)

Get probeset data matrix/matrices:

set <- RPA::get.probeset("Actinomyces naeslundii", "species",
                 taxonomy, probedata, log10 = TRUE)