map_taxa {chem16S}R Documentation

Map taxonomic names to NCBI or GTDB taxonomy


Maps taxonomic names to NCBI (RefSeq) or GTDB taxonomy by automatic matching of taxonomic names, with manual mappings for some groups.


  map_taxa(taxacounts = NULL, refdb = "GTDB_214", taxon_AA = NULL, quiet = FALSE)



data frame with taxonomic name and abundances


character, name of reference database (‘⁠GTDB_214⁠’ or ‘⁠RefSeq_206⁠’)


data frame, amino acid compositions of taxa, used to bypass refdb specification


logical, suppress printed messages?


This function maps taxonomic names to the NCBI (RefSeq) or GTDB taxonomy. taxacounts should be a data frame generated by either read_RDP or ps_taxacounts. Input names are made by combining the taxonomic rank and name with an underscore separator (e.g. ‘⁠genus_ Escherichia/Shigella⁠’). Input names are then matched to the taxa listed in ‘taxon_AA.csv.xz’ found under ‘RefDB/RefSeq_206’ or ‘RefDB/GTDB_214’. The protein and organism columns in these files hold the rank and taxon name extracted from the RefSeq or GTDB database. Only exactly matching names are automatically mapped.

For mapping to the NCBI (RefSeq) taxonomy, some group names are manually mapped as follows (see Dick and Tan, 2023):

RDP training set NCBI
genus_Escherichia/Shigella genus_Escherichia
phylum_Cyanobacteria/Chloroplast phylum_Cyanobacteria
genus_Marinimicrobia_genera_incertae_sedis species_Candidatus Marinimicrobia bacterium
class_Cyanobacteria phylum_Cyanobacteria
genus_Spartobacteria_genera_incertae_sedis species_Spartobacteria bacterium LR76
class_Planctomycetacia class_Planctomycetia
class_Actinobacteria phylum_Actinobacteria
order_Rhizobiales order_Hyphomicrobiales
genus_Gp1 genus_Acidobacterium
genus_Gp6 genus_Luteitalea
genus_GpI genus_Nostoc
genus_GpIIa genus_Synechococcus
genus_GpVI genus_Pseudanabaena
family_Family II family_Synechococcaceae
genus_Subdivision3_genera_incertae_sedis family_Verrucomicrobia subdivision 3
order_Clostridiales order_Eubacteriales
family_Ruminococcaceae family_Oscillospiraceae

To avoid manual mapping, GTDB can be used for both taxonomic assignemnts and reference proteomes. Taxonomic assignments based on 16S rRNA sequences from GTDB can be made using training files for the RDP Classifier (doi:10.5281/zenodo.7633099) or dada2 (doi:10.5281/zenodo.2541238) (make sure to choose the appropriate GTDB version). Example files created using the RDP Classifier are provided under ‘extdata/RDP-GTDB_207’. An example dataset created with DADA2 is data(mouse.GTDB_214); this is a phyloseq-class object that can be processed with functions described at physeq.

Change quiet to TRUE to suppress printing of messages about manual mappings, most abundant unmapped groups, and overall percentage of mapped names.


Integer vector with length equal to number of rows of taxacounts. Values are rownumbers in the data frame generated by reading taxon_AA.csv.xz, or NA for no matching taxon. Attributes unmapped_groups and unmapped_percent have the input names of unmapped groups and their percentage of the total classification count.


Dick JM, Tan J. 2023. Chemical links between redox conditions and estimated community proteomes from 16S rRNA and reference protein sequences. Microbial Ecology 85: 1338–1355. doi:10.1007/s00248-022-01988-9


# Mapping taxonomic classifications from RDP training set to NCBI taxonomy
file <- system.file("extdata/RDP/", package = "chem16S")
RDP <- read_RDP(file)
map <- map_taxa(RDP, refdb = "RefSeq_206")
# About 24% of classifications are unmapped

# Mapping from GTDB training set to GTDB taxonomy
file <- system.file("extdata/RDP-GTDB_207/", package = "chem16S")
RDP.GTDB <- read_RDP(file)
map.GTDB <- map_taxa(RDP.GTDB)
# The classifications were made with GTDB r207, but the reference database 
# in chem16S has been updated to GTDB r214, so the mapping rate is less than 100 %

[Package chem16S version 1.1.0 Index]