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@grabear
Last active September 18, 2020 13:01
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Parsing .biom files with SILVA formatted annotations using phyloseq
#' @examples
#' taxvec1 = c("Root", "k__Bacteria", "p__Firmicutes", "c__Bacilli", "o__Bacillales", "f__Staphylococcaceae")
#' parse_taxonomy_default(taxvec1)
parse_taxonomy_default = function(char.vec){
# Remove any leading empty space
char.vec = gsub("^[[:space:]]{1,}", "", char.vec)
# Remove any trailing space
char.vec = gsub("[[:space:]]{1,}$", "", char.vec)
if( length(char.vec) > 0 ){
# Add dummy element (rank) name
names(char.vec) = paste("Rank", 1:length(char.vec), sep="")
} else {
warning("Empty taxonomy vector encountered.")
}
return(char.vec)
}
#' @examples
#' taxvec3 = c("D_0__Bacteria", "D_1__Firmicutes", "D_2__Bacilli", "D_3__Staphylococcaceae")
#' parse_taxonomy_silva(taxvec3)
parse_taxonomy_silva_128 <- function(char.vec){
# Use default to assign names to elements in case problem with greengenes prefix
char.vec = parse_taxonomy_default(char.vec)
# Check for unassigned taxa
if (char.vec["Rank1"] == "Unassigned") {
char.vec <- c(Rank1="D_0__Unassigned", Rank2="D_1__Unassigned", Rank3="D_2__Unassigned", Rank4="D_3__Unassigned",
Rank5="D_4__Unassigned", Rank6="D_5__Unassigned", Rank7="D_6__Unassigned")
}
# Define the meaning of each prefix according to SILVA taxonomy
Tranks = c(D_0="Kingdom", D_1="Phylum", D_2="Class", D_3="Order", D_4="Family", D_5="Genus", D_6="Species")
# Check for prefix using regexp, warn if there were none. trim indices, ti
ti = grep("[[:alpha:]]\\_[[:digit:]]{1}\\_\\_", char.vec)
if( length(ti) == 0L ){
warning(
"No silva prefixes were found. \n",
"Consider using parse_taxonomy_delfault() instead if true for all OTUs. \n",
"Dummy ranks may be included among taxonomic ranks now."
)
# Will want to return without further modifying char.vec
taxvec = char.vec
# Replace names of taxvec according to prefix, if any present...
} else {
# Format character vectors for Ambiguous taxa
if( length(ti) < 7 ){
for (key in names(char.vec)) {
if ( char.vec[key] == "Ambiguous_taxa" ) {
tax_no <- (as.numeric(substr(key, 5, 5)) - 1)
char.vec[key] = sprintf("D_%s__Ambiguous_taxa", tax_no)
}
}
# Reset the trimmed indicies if Ambiguous taxa
ti = grep("[[:alpha:]]\\_[[:digit:]]{1}\\_\\_", char.vec)
}
# Remove prefix using sub-"" regexp, call result taxvec
taxvec = gsub("[[:alpha:]]\\_[[:digit:]]{1}\\_\\_", "", char.vec)
# Define the ranks that will be replaced
repranks = Tranks[substr(char.vec[ti], 1, 3)]
# Replace, being sure to avoid prefixes notK present in Tranks
names(taxvec)[ti[!is.na(repranks)]] = repranks[!is.na(repranks)]
}
return(taxvec)
}
# This functionality has been tested and a PR has been pulled with phyloseq here:
# https://github.com/joey711/phyloseq/pull/854
#
# While the function has been vetted, the maintainers are very busy and the PR has not
# yet been added to the main package. Below i've added some detail to explain how to parse
# your silva data. It's quite easy....
source("parse_silva_taxonomy_128")
# import biom data
silva_biom <- system.file("extdata", "SILVA_OTU_table.biom", package="phyloseq")
# Create phyloseq object using silva parseing function
silva_phyloseq <- import_biom(BIOMfilename = silva_biom, parseFunction = parse_taxonomy_silva_128)
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grabear commented Dec 12, 2019

Nice. I'm not sure what the Silva132 data looks like as I haven't done any work with it yet. These may be relevant ranks that the Silva132 database uses, but my function just doesn't parse it out. I'd be interested to see what your Silva132 data looks like. Feel free to post a sample of your data here (or a link to it) @gcagle1 @samd1993. You can also find a ton of great functions (including this one) in a package that I authored a while back https://github.com/vallenderlab/MicrobiomeR. The documentation website is currently down, but once I get it working again I will let you guys know here.

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