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Import and Process Resistance Gene Identifier (RGI) Results

Source: R/import_geno.R
import_rgi.Rd

This function imports and processes genotyping results from the Resistance Gene Identifier (RGI, https://github.com/arpcard/rgi), extracting antimicrobial resistance determinants and mapping them to standardised drug classes/antibiotics.

Usage

import_rgi(
  input_table,
  orf_id_col = "ORF_ID",
  sample_id_sep = ".fasta.txt:",
  model_col = "Model_type",
  antibiotic_col = "Antibiotic",
  class_col = "Drug Class",
  exclude_loose = TRUE,
  rgi_short_name = rgi_short_name_table,
  rgi_drugs = rgi_drugs_table,
  samples_no_amr = NULL
)

Arguments

input_table

A character string specifying a dataframe or path to the RGI results table (TSV format).

orf_id_col

A character string specifying the column that identifies open reading frame ID (ORF_ID) in the dataset (default ORF_ID). This column includes the sample ID and the contig / genomic location and is a default output of RGI.

sample_id_sep

A character string specifying the separator by which the sample ID is separated from the remaining text in ORF_ID (Default: .fasta.txt:) . For example: in the ORF_ID column, "SAMEA3498968.fasta.txt:1_96 # 109511 # 110635....", the sample ID separator is .fasta.txt:.

model_col

A character string specifying the column that identifies model type identified by RGI (default Model_type).

antibiotic_col

Character string specifying the antibiotic column (default Antibiotic).

class_col

Character string specifying the drug class column (default Drug Class).

exclude_loose

Logical indicating whether to exclude Loose hits (AMR markers that fall below a curated bitscore cutoff as defined by CARD/RGI). Default TRUE, which excludes Loose hits.

rgi_short_name

A tibble containing a reference table mapping model IDs (from CARD/RGI) to shortened model names as provided by CARD (https://card.mcmaster.ca/download in aro_index.tsv). Defaults to rgi_short_name_table, which is provided internally.

rgi_drugs

A tibble containing a reference table mapping CARD drug class / drug agents to standardised drug classes/names. Defaults to rgi_drugs_table, which is provided internally.

samples_no_amr

A vector of sample IDs that have no RGI output because there are no AMR markers identified. For example c("SampleA", "SampleB"). (default = NULL)

Value

A tibble containing the processed AMR determinants and drug classes that is AMRgen compatible. The output retains the original columns from the RGI output along with the newly mapped variables.

Details

The function performs the following steps:

  • Reads the RGI output table.

  • Transforms RGI output into long form (i.e., one AMR determinant AND drug class / antibiotic per row).

  • Maps CARD drug classes and antibiotics to standardised names. This processing ensures compatibility with downstream AMRgen analysis workflows.

Examples

# example RGI data (including Perfect, Strict, and Loose hits)
rgi_raw
#> # A tibble: 21,203 × 29
#>    ORF_ID Contig Start  Stop Orientation Cut_Off Pass_Bitscore Best_Hit_Bitscore
#>    <chr>  <chr>  <dbl> <dbl> <chr>       <chr>           <dbl>             <dbl>
#>  1 GCA_0… JASER…     2   283 +           Loose            1150              24.3
#>  2 GCA_0… JASER…   367  1662 +           Loose             700             172. 
#>  3 GCA_0… JASER…  1666  1989 -           Loose             500              23.5
#>  4 GCA_0… JASER…  2031  3386 -           Loose            1900              29.3
#>  5 GCA_0… JASER…  3507  6158 -           Loose             275              30.4
#>  6 GCA_0… JASER…  6961  7386 -           Loose             910              25.4
#>  7 GCA_0… JASER…  7590  8675 +           Loose             450              45.8
#>  8 GCA_0… JASER…  9735 10118 +           Loose             600              25.8
#>  9 GCA_0… JASER… 10164 11495 -           Loose             500              26.6
#> 10 GCA_0… JASER… 11627 12364 +           Loose             400              37.7
#> # ℹ 21,193 more rows
#> # ℹ 21 more variables: Best_Hit_ARO <chr>, Best_Identities <dbl>, ARO <dbl>,
#> #   Model_type <chr>, SNPs_in_Best_Hit_ARO <chr>, Other_SNPs <chr>,
#> #   `Drug Class` <chr>, `Resistance Mechanism` <chr>, `AMR Gene Family` <chr>,
#> #   Predicted_DNA <chr>, Predicted_Protein <chr>, CARD_Protein_Sequence <chr>,
#> #   `Percentage Length of Reference Sequence` <dbl>, ID <chr>, Model_ID <dbl>,
#> #   Nudged <lgl>, Note <lgl>, Hit_Start <dbl>, Hit_End <dbl>, …

# import using sample_id_sep=`_genomic.fna.txt:` and include Loose hits
rgi <- import_rgi(rgi_raw, sample_id_sep = "_genomic.fna.txt:", exclude_loose = FALSE)

# example RGI data from EuSCAPE project (including only Perfect and Strict hits)
rgi_EuSCAPE_raw
#> # A tibble: 59,447 × 26
#>    ORF_ID                 Contig  Start   Stop Orientation Cut_Off Pass_Bitscore
#>    <chr>                   <dbl>  <dbl>  <dbl> <chr>       <chr>           <dbl>
#>  1 SAMEA3498968.fasta.tx…      1 109511 110635 -           Strict            700
#>  2 SAMEA3498968.fasta.tx…      1 237710 238072 +           Perfect           150
#>  3 SAMEA3498968.fasta.tx…      1 238059 238388 +           Perfect           150
#>  4 SAMEA3498968.fasta.tx…      1 278325 279185 -           Perfect           550
#>  5 SAMEA3498968.fasta.tx…      1 299277 299651 -           Strict            230
#>  6 SAMEA3498968.fasta.tx…      2 120780 123893 -           Strict           1900
#>  7 SAMEA3498968.fasta.tx…      2 379306 380745 +           Perfect           900
#>  8 SAMEA3498968.fasta.tx…      2 437973 441050 -           Strict           1800
#>  9 SAMEA3498968.fasta.tx…      2 441051 444173 -           Strict           1800
#> 10 SAMEA3498968.fasta.tx…      3 347739 348971 +           Strict            700
#> # ℹ 59,437 more rows
#> # ℹ 19 more variables: Best_Hit_Bitscore <dbl>, Best_Hit_ARO <chr>,
#> #   Best_Identities <dbl>, ARO <dbl>, Model_type <chr>,
#> #   SNPs_in_Best_Hit_ARO <chr>, Other_SNPs <chr>, `Drug Class` <chr>,
#> #   `Resistance Mechanism` <chr>, `AMR Gene Family` <chr>,
#> #   `Percentage Length of Reference Sequence` <dbl>, ID <chr>, Model_ID <dbl>,
#> #   Nudged <lgl>, Note <lgl>, Hit_Start <dbl>, Hit_End <dbl>, …

# import using defaults (sample_id_sep=`.fasta.txt:`, exclude_loose = `TRUE`)
import_rgi(rgi_EuSCAPE_raw)
#> # A tibble: 293,017 × 33
#>    id      marker mutation drug  drug_class `variation type` marker.label ORF_ID
#>    <chr>   <chr>  <chr>    <chr> <chr>      <chr>            <chr>        <chr> 
#>  1 SAMEA3… Klebs… NA       FOX   Cephalosp… Gene presence d… Kpne_OmpK37… SAMEA…
#>  2 SAMEA3… Klebs… NA       CTX   Cephalosp… Gene presence d… Kpne_OmpK37… SAMEA…
#>  3 SAMEA3… Klebs… NA       ERY   Macrolides Gene presence d… Kpne_KpnE    SAMEA…
#>  4 SAMEA3… Klebs… NA       STR1  Aminoglyc… Gene presence d… Kpne_KpnE    SAMEA…
#>  5 SAMEA3… Klebs… NA       TCY   Tetracycl… Gene presence d… Kpne_KpnE    SAMEA…
#>  6 SAMEA3… Klebs… NA       FEP   Cephalosp… Gene presence d… Kpne_KpnE    SAMEA…
#>  7 SAMEA3… Klebs… NA       CRO   Cephalosp… Gene presence d… Kpne_KpnE    SAMEA…
#>  8 SAMEA3… Klebs… NA       RIF   Rifamycins Gene presence d… Kpne_KpnE    SAMEA…
#>  9 SAMEA3… Klebs… NA       COL   Polymyxins Gene presence d… Kpne_KpnE    SAMEA…
#> 10 SAMEA3… Klebs… NA       COL   Polymyxins Gene presence d… Kpne_KpnE    SAMEA…
#> # ℹ 293,007 more rows
#> # ℹ 25 more variables: Contig <dbl>, Start <dbl>, Stop <dbl>,
#> #   Orientation <chr>, Cut_Off <chr>, Pass_Bitscore <dbl>,
#> #   Best_Hit_Bitscore <dbl>, Best_Hit_ARO <chr>, Best_Identities <dbl>,
#> #   ARO <dbl>, Model_type <chr>, Other_SNPs <chr>, `Drug Class` <chr>,
#> #   `Resistance Mechanism` <chr>, `AMR Gene Family` <chr>,
#> #   `Percentage Length of Reference Sequence` <dbl>, ID <chr>, …