assign_tax {demulticoder} | R Documentation |
Assign taxonomy functions
Description
Assign taxonomy functions
Usage
assign_tax(
analysis_setup,
asv_abund_matrix,
retrieve_files = FALSE,
overwrite_existing = FALSE,
db_rps10 = "oomycetedb.fasta",
db_its = "fungidb.fasta",
db_16S = "bacteriadb.fasta",
db_other1 = "otherdb1.fasta",
db_other2 = "otherdb2.fasta"
)
Arguments
analysis_setup |
An object containing directory paths and data tables,
produced by the |
asv_abund_matrix |
The final abundance matrix containing amplified sequence variants |
retrieve_files |
Logical, TRUE/FALSE whether to copy files from the temp directory to the output directory. Default is FALSE. |
overwrite_existing |
Logical, indicating whether to remove or overwrite
existing files and directories from previous runs. Default is |
db_rps10 |
The reference database for the rps10 metabarcode |
db_its |
The reference database for the ITS metabarcode |
db_16S |
The SILVA 16S-rRNA reference database provided by the user |
db_other1 |
The reference database for other metabarcode 1 (assumes format is like SILVA DB entries) |
db_other2 |
The reference database for other metabarcode 2 (assumes format is like SILVA DB entries) |
Details
At this point, 'DADA2' function assignTaxonomy is used to assign taxonomy to the inferred ASVs.
Value
Taxonomic assignments of each unique ASV sequence
Examples
# Assign taxonomies to ASVs on by metabarcode
analysis_setup <- prepare_reads(
data_directory = system.file("extdata", package = "demulticoder"),
output_directory = tempdir(),
overwrite_existing = TRUE
)
cut_trim(
analysis_setup,
cutadapt_path="/usr/bin/cutadapt",
overwrite_existing = TRUE
)
make_asv_abund_matrix(
analysis_setup,
overwrite_existing = TRUE
)
assign_tax(
analysis_setup,
asv_abund_matrix,
retrieve_files=FALSE,
overwrite_existing = TRUE
)