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fix `reference_df` endless loop

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dr. M.S. (Matthijs) Berends 2023-06-26 13:52:02 +02:00
parent 1d9ee39cc7
commit 2d97cca6d9
29 changed files with 215 additions and 200 deletions
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DESCRIPTION
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Package: AMR Package: AMR
Version: 2.0.0.9025 Version: 2.0.0.9026
Date: 2023-06-22 Date: 2023-06-26
Title: Antimicrobial Resistance Data Analysis Title: Antimicrobial Resistance Data Analysis
Description: Functions to simplify and standardise antimicrobial resistance (AMR) Description: Functions to simplify and standardise antimicrobial resistance (AMR)
data analysis and to work with microbial and antimicrobial properties by data analysis and to work with microbial and antimicrobial properties by

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NEWS.md
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# AMR 2.0.0.9025 # AMR 2.0.0.9026
## New ## New
* Clinical breakpoints and intrinsic resistance of EUCAST 2023 and CLSI 2023 have been added for `as.sir()`. EUCAST 2023 (v13.0) is now the new default guideline for all MIC and disks diffusion interpretations, and for `eucast_rules()` to apply EUCAST Expert Rules. * Clinical breakpoints and intrinsic resistance of EUCAST 2023 and CLSI 2023 have been added for `as.sir()`. EUCAST 2023 (v13.0) is now the new default guideline for all MIC and disks diffusion interpretations, and for `eucast_rules()` to apply EUCAST Expert Rules.
@ -22,6 +22,7 @@
* Fix for using the `keep_synonyms` argument when using MO codes as input * Fix for using the `keep_synonyms` argument when using MO codes as input
* Fix for using the `minimum_matching_score` argument * Fix for using the `minimum_matching_score` argument
* Updated the code table in `microorganisms.codes` * Updated the code table in `microorganisms.codes`
* Fixed an endless loop if using `reference_df` in `as.mo()`
# AMR 2.0.0 # AMR 2.0.0

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R/mo.R
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@ -1217,7 +1217,7 @@ repair_reference_df <- function(reference_df) {
reference_df[, "mo"] <- as.character(reference_df[, "mo", drop = TRUE]) reference_df[, "mo"] <- as.character(reference_df[, "mo", drop = TRUE])
# some MO codes might be old # some MO codes might be old
reference_df[, "mo"] <- as.mo(reference_df[, "mo", drop = TRUE]) reference_df[, "mo"] <- as.mo(reference_df[, "mo", drop = TRUE], reference_df = NULL)
reference_df reference_df
} }

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data-raw/_language_update.R
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# ==================================================================== # # ==================================================================== #
# TITLE # # TITLE: #
# AMR: An R Package for Working with Antimicrobial Resistance Data # # AMR: An R Package for Working with Antimicrobial Resistance Data #
# # # #
# SOURCE # # SOURCE CODE: #
# https://github.com/msberends/AMR # # https://github.com/msberends/AMR #
# # # #
# CITE AS # # PLEASE CITE THIS SOFTWARE AS: #
# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C # # Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
# (2022). AMR: An R Package for Working with Antimicrobial Resistance # # (2022). AMR: An R Package for Working with Antimicrobial Resistance #
# Data. Journal of Statistical Software, 104(3), 1-31. # # Data. Journal of Statistical Software, 104(3), 1-31. #

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data-raw/_pre_commit_hook.R
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# ==================================================================== # # ==================================================================== #
# TITLE # # TITLE: #
# AMR: An R Package for Working with Antimicrobial Resistance Data # # AMR: An R Package for Working with Antimicrobial Resistance Data #
# # # #
# SOURCE # # SOURCE CODE: #
# https://github.com/msberends/AMR # # https://github.com/msberends/AMR #
# # # #
# CITE AS # # PLEASE CITE THIS SOFTWARE AS: #
# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C # # Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
# (2022). AMR: An R Package for Working with Antimicrobial Resistance # # (2022). AMR: An R Package for Working with Antimicrobial Resistance #
# Data. Journal of Statistical Software, 104(3), 1-31. # # Data. Journal of Statistical Software, 104(3), 1-31. #

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data-raw/loinc.R
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# ==================================================================== # # ==================================================================== #
# TITLE # # TITLE: #
# AMR: An R Package for Working with Antimicrobial Resistance Data # # AMR: An R Package for Working with Antimicrobial Resistance Data #
# # # #
# SOURCE # # SOURCE CODE: #
# https://github.com/msberends/AMR # # https://github.com/msberends/AMR #
# # # #
# CITE AS # # PLEASE CITE THIS SOFTWARE AS: #
# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C # # Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
# (2022). AMR: An R Package for Working with Antimicrobial Resistance # # (2022). AMR: An R Package for Working with Antimicrobial Resistance #
# Data. Journal of Statistical Software, 104(3), 1-31. # # Data. Journal of Statistical Software, 104(3), 1-31. #

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data-raw/microorganisms.md5
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data-raw/microorganisms.txt
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@ -547,6 +547,7 @@
"B_ACNTB_AVST" "Acinetobacter avistercoris" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Pseudomonadales" "Moraxellaceae" "Acinetobacter" "avistercoris" "" "species" "likely facultative anaerobe" "GBIF" "11605583" "3223263" 1.5 "" "B_ACNTB_AVST" "Acinetobacter avistercoris" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Pseudomonadales" "Moraxellaceae" "Acinetobacter" "avistercoris" "" "species" "likely facultative anaerobe" "GBIF" "11605583" "3223263" 1.5 ""
"B_ACNTB_BART" "Acinetobacter baretiae" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Pseudomonadales" "Moraxellaceae" "Acinetobacter" "baretiae" "" "species" "Alvarez-Perez et al., 2021" "likely facultative anaerobe" "LPSN" "19553" "515021" "11852261" "3223263" 1.5 "" "B_ACNTB_BART" "Acinetobacter baretiae" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Pseudomonadales" "Moraxellaceae" "Acinetobacter" "baretiae" "" "species" "Alvarez-Perez et al., 2021" "likely facultative anaerobe" "LPSN" "19553" "515021" "11852261" "3223263" 1.5 ""
"B_ACNTB_BMNN" "Acinetobacter baumannii" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Pseudomonadales" "Moraxellaceae" "Acinetobacter" "baumannii" "" "species" "Bouvet et al., 1986" "aerobe" "LPSN" "772610" "515021" "3223274" "3223263" 1 "91288006,715174007,737526007,447891000124105,715353004" "B_ACNTB_BMNN" "Acinetobacter baumannii" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Pseudomonadales" "Moraxellaceae" "Acinetobacter" "baumannii" "" "species" "Bouvet et al., 1986" "aerobe" "LPSN" "772610" "515021" "3223274" "3223263" 1 "91288006,715174007,737526007,447891000124105,715353004"
"B_ACNTB_BMNN-C" "Acinetobacter baumannii complex" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Pseudomonadales" "Moraxellaceae" "Acinetobacter" "baumannii complex" "" "species group" "aerobe" "manually added" "515021" "3223263" 1 ""
"B_ACNTB_BYLY" "Acinetobacter baylyi" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Pseudomonadales" "Moraxellaceae" "Acinetobacter" "baylyi" "" "species" "Carr et al., 2003" "aerobe" "LPSN" "772611" "515021" "3223268" "3223263" 1 "423974000" "B_ACNTB_BYLY" "Acinetobacter baylyi" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Pseudomonadales" "Moraxellaceae" "Acinetobacter" "baylyi" "" "species" "Carr et al., 2003" "aerobe" "LPSN" "772611" "515021" "3223268" "3223263" 1 "423974000"
"B_ACNTB_BJRN" "Acinetobacter beijerinckii" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Pseudomonadales" "Moraxellaceae" "Acinetobacter" "beijerinckii" "" "species" "Nemec et al., 2009" "aerobe" "LPSN" "787668" "515021" "8317472" "3223263" 1 "771547006" "B_ACNTB_BJRN" "Acinetobacter beijerinckii" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Pseudomonadales" "Moraxellaceae" "Acinetobacter" "beijerinckii" "" "species" "Nemec et al., 2009" "aerobe" "LPSN" "787668" "515021" "8317472" "3223263" 1 "771547006"
"B_ACNTB_BERZN" "Acinetobacter berezinae" "synonym" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Pseudomonadales" "Moraxellaceae" "Acinetobacter" "berezinae" "" "species" "Alexandr et al., 2009" "aerobe" "GBIF" "9467748" "3223263" "7798724" 1 "" "B_ACNTB_BERZN" "Acinetobacter berezinae" "synonym" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Pseudomonadales" "Moraxellaceae" "Acinetobacter" "berezinae" "" "species" "Alexandr et al., 2009" "aerobe" "GBIF" "9467748" "3223263" "7798724" 1 ""
@ -8476,6 +8477,7 @@
"B_BRKHL_CATD" "Burkholderia catudaia" "synonym" "Bacteria" "Pseudomonadota" "Betaproteobacteria" "Burkholderiales" "Burkholderiaceae" "Burkholderia" "catudaia" "" "species" "Peeters et al., 2016" "aerobe" "LPSN" "794437" "515281" "796021" "9576146" "3219916" 1.5 "" "B_BRKHL_CATD" "Burkholderia catudaia" "synonym" "Bacteria" "Pseudomonadota" "Betaproteobacteria" "Burkholderiales" "Burkholderiaceae" "Burkholderia" "catudaia" "" "species" "Peeters et al., 2016" "aerobe" "LPSN" "794437" "515281" "796021" "9576146" "3219916" 1.5 ""
"B_BRKHL_CNCP" "Burkholderia cenocepacia" "accepted" "Bacteria" "Pseudomonadota" "Betaproteobacteria" "Burkholderiales" "Burkholderiaceae" "Burkholderia" "cenocepacia" "" "species" "Vandamme et al., 2003" "aerobe" "LPSN" "774276" "515281" "10898083" "3219916" 1 "416941006" "B_BRKHL_CNCP" "Burkholderia cenocepacia" "accepted" "Bacteria" "Pseudomonadota" "Betaproteobacteria" "Burkholderiales" "Burkholderiaceae" "Burkholderia" "cenocepacia" "" "species" "Vandamme et al., 2003" "aerobe" "LPSN" "774276" "515281" "10898083" "3219916" 1 "416941006"
"B_BRKHL_CEPC" "Burkholderia cepacia" "accepted" "Bacteria" "Pseudomonadota" "Betaproteobacteria" "Burkholderiales" "Burkholderiaceae" "Burkholderia" "cepacia" "" "species" "Yabuuchi et al., 1993" "aerobe" "LPSN" "774277" "515281" "10900882" "3219916" 1 "113669008" "B_BRKHL_CEPC" "Burkholderia cepacia" "accepted" "Bacteria" "Pseudomonadota" "Betaproteobacteria" "Burkholderiales" "Burkholderiaceae" "Burkholderia" "cepacia" "" "species" "Yabuuchi et al., 1993" "aerobe" "LPSN" "774277" "515281" "10900882" "3219916" 1 "113669008"
"B_BRKHL_CEPC-C" "Burkholderia cepacia complex" "accepted" "Bacteria" "Pseudomonadota" "Betaproteobacteria" "Burkholderiales" "Burkholderiaceae" "Burkholderia" "cepacia complex" "" "species group" "aerobe" "manually added" "515281" "3219916" 1 ""
"B_BRKHL_CHOC" "Burkholderia choica" "synonym" "Bacteria" "Pseudomonadota" "Betaproteobacteria" "Burkholderiales" "Burkholderiaceae" "Burkholderia" "choica" "" "species" "Vandamme et al., 2013" "aerobe" "LPSN" "791329" "515281" "794372" 1.5 "" "B_BRKHL_CHOC" "Burkholderia choica" "synonym" "Bacteria" "Pseudomonadota" "Betaproteobacteria" "Burkholderiales" "Burkholderiaceae" "Burkholderia" "choica" "" "species" "Vandamme et al., 2013" "aerobe" "LPSN" "791329" "515281" "794372" 1.5 ""
"B_BRKHL_CCVN" "Burkholderia cocovenenans" "synonym" "Bacteria" "Pseudomonadota" "Betaproteobacteria" "Burkholderiales" "Burkholderiaceae" "Burkholderia" "cocovenenans" "" "species" "Gillis et al., 1995" "aerobe" "LPSN" "7156" "515281" "774282" "3219917" "3219916" "3219971" 1 "" "B_BRKHL_CCVN" "Burkholderia cocovenenans" "synonym" "Bacteria" "Pseudomonadota" "Betaproteobacteria" "Burkholderiales" "Burkholderiaceae" "Burkholderia" "cocovenenans" "" "species" "Gillis et al., 1995" "aerobe" "LPSN" "7156" "515281" "774282" "3219917" "3219916" "3219971" 1 ""
"B_BRKHL_CNCT" "Burkholderia concitans" "synonym" "Bacteria" "Pseudomonadota" "Betaproteobacteria" "Burkholderiales" "Burkholderiaceae" "Burkholderia" "concitans" "" "species" "Peeters et al., 2016" "aerobe" "LPSN" "794438" "515281" "796022" "9429304" "3219916" 1.5 "" "B_BRKHL_CNCT" "Burkholderia concitans" "synonym" "Bacteria" "Pseudomonadota" "Betaproteobacteria" "Burkholderiales" "Burkholderiaceae" "Burkholderia" "concitans" "" "species" "Peeters et al., 2016" "aerobe" "LPSN" "794438" "515281" "796022" "9429304" "3219916" 1.5 ""
@ -9058,6 +9060,7 @@
"F_CANDD_ALBC" "Candida albicans" "accepted" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "albicans" "" "species" "Berkhout" "GBIF" "2599597" "2518121" 1.5 "53326005,243448008,714313009" "F_CANDD_ALBC" "Candida albicans" "accepted" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "albicans" "" "species" "Berkhout" "GBIF" "2599597" "2518121" 1.5 "53326005,243448008,714313009"
"F_CANDD_ALBC_ALBC" "Candida albicans albicans" "synonym" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "albicans" "albicans" "subspecies" "GBIF" "11228679" "2599597" "2599597" 1.5 "" "F_CANDD_ALBC_ALBC" "Candida albicans albicans" "synonym" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "albicans" "albicans" "subspecies" "GBIF" "11228679" "2599597" "2599597" 1.5 ""
"F_CANDD_ALBC_CLSS" "Candida albicans claussenii" "synonym" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "albicans" "claussenii" "subspecies" "Lodder et al." "GBIF" "11281986" "2599597" "2599597" 1.5 "" "F_CANDD_ALBC_CLSS" "Candida albicans claussenii" "synonym" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "albicans" "claussenii" "subspecies" "Lodder et al." "GBIF" "11281986" "2599597" "2599597" 1.5 ""
"F_CANDD_ALBC-C" "Candida albicans complex" "accepted" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "albicans complex" "" "species group" "manually added" "2518121" 1.5 ""
"F_CANDD_ALBC_MTLN" "Candida albicans metalondinensis" "synonym" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "albicans" "metalondinensis" "subspecies" "Castell et al." "GBIF" "11270252" "2599597" "2599597" 1.5 "" "F_CANDD_ALBC_MTLN" "Candida albicans metalondinensis" "synonym" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "albicans" "metalondinensis" "subspecies" "Castell et al." "GBIF" "11270252" "2599597" "2599597" 1.5 ""
"F_CANDD_ALBC_NNLQ" "Candida albicans non-liquefaciens" "synonym" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "albicans" "non-liquefaciens" "subspecies" "Sasak" "GBIF" "11323433" "2599597" "2599597" 1.5 "" "F_CANDD_ALBC_NNLQ" "Candida albicans non-liquefaciens" "synonym" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "albicans" "non-liquefaciens" "subspecies" "Sasak" "GBIF" "11323433" "2599597" "2599597" 1.5 ""
"F_CANDD_ALBC_STLL" "Candida albicans stellatoidea" "synonym" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "albicans" "stellatoidea" "subspecies" "Jones et al." "GBIF" "11340449" "2599597" "2599597" 1.5 "" "F_CANDD_ALBC_STLL" "Candida albicans stellatoidea" "synonym" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "albicans" "stellatoidea" "subspecies" "Jones et al." "GBIF" "11340449" "2599597" "2599597" 1.5 ""
@ -9216,6 +9219,7 @@
"F_CANDD_FNSS" "Candida gifuensis" "synonym" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "gifuensis" "" "species" "Tanig" "GBIF" "5495793" "2518121" "2599597" 1.5 "" "F_CANDD_FNSS" "Candida gifuensis" "synonym" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "gifuensis" "" "species" "Tanig" "GBIF" "5495793" "2518121" "2599597" 1.5 ""
"F_CANDD_GGNT" "Candida gigantensis" "accepted" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "gigantensis" "" "species" "Suh et al." "GBIF" "3480169" "2518121" 1.5 "" "F_CANDD_GGNT" "Candida gigantensis" "accepted" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "gigantensis" "" "species" "Suh et al." "GBIF" "3480169" "2518121" 1.5 ""
"F_CANDD_GLBR" "Candida glabrata" "accepted" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "glabrata" "" "species" "Mey et al." "GBIF" "2599530" "2518121" 1.5 "444877006,782948004" "F_CANDD_GLBR" "Candida glabrata" "accepted" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "glabrata" "" "species" "Mey et al." "GBIF" "2599530" "2518121" 1.5 "444877006,782948004"
"F_CANDD_GLBR-C" "Candida glabrata complex" "accepted" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "glabrata complex" "" "species group" "manually added" "2518121" 1.5 ""
"F_CANDD_BRTS" "Candida glabratus" "synonym" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "glabratus" "" "species" "Anderson" "GBIF" "7407691" "2518121" "2599530" 1.5 "" "F_CANDD_BRTS" "Candida glabratus" "synonym" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "glabratus" "" "species" "Anderson" "GBIF" "7407691" "2518121" "2599530" 1.5 ""
"F_CANDD_GLBS" "Candida glaebosa" "accepted" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "glaebosa" "" "species" "Komag et al." "GBIF" "3480310" "2518121" 1.5 "" "F_CANDD_GLBS" "Candida glaebosa" "accepted" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "glaebosa" "" "species" "Komag et al." "GBIF" "3480310" "2518121" 1.5 ""
"F_CANDD_LBSM" "Candida globosum" "synonym" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "globosum" "" "species" "Zach" "GBIF" "3480508" "2518121" "2599539" 1.5 "" "F_CANDD_LBSM" "Candida globosum" "synonym" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "globosum" "" "species" "Zach" "GBIF" "3480508" "2518121" "2599539" 1.5 ""
@ -9390,6 +9394,7 @@
"F_CANDD_PRPL" "Candida parapolymorpha" "accepted" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "parapolymorpha" "" "species" "Suh et al." "GBIF" "8157046" "2518121" 1.5 "" "F_CANDD_PRPL" "Candida parapolymorpha" "accepted" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "parapolymorpha" "" "species" "Suh et al." "GBIF" "8157046" "2518121" 1.5 ""
"F_CANDD_PRPSL" "Candida parapsilopsis" "synonym" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "parapsilopsis" "" "species" "Ashford" "GBIF" "2599545" "2518121" "2599539" 1.5 "" "F_CANDD_PRPSL" "Candida parapsilopsis" "synonym" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "parapsilopsis" "" "species" "Ashford" "GBIF" "2599545" "2518121" "2599539" 1.5 ""
"F_CANDD_PRPS" "Candida parapsilosis" "accepted" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "parapsilosis" "" "species" "Langeron et al." "GBIF" "2599539" "2518121" 1.5 "61302002" "F_CANDD_PRPS" "Candida parapsilosis" "accepted" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "parapsilosis" "" "species" "Langeron et al." "GBIF" "2599539" "2518121" 1.5 "61302002"
"F_CANDD_PRPS-C" "Candida parapsilosis complex" "accepted" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "parapsilosis complex" "" "species group" "manually added" "2518121" 1.5 ""
"F_CANDD_PRPS_HOKK" "Candida parapsilosis hokkaii" "synonym" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "parapsilosis" "hokkaii" "subspecies" "Goto et al." "GBIF" "3480002" "2599539" "3479947" 1.5 "" "F_CANDD_PRPS_HOKK" "Candida parapsilosis hokkaii" "synonym" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "parapsilosis" "hokkaii" "subspecies" "Goto et al." "GBIF" "3480002" "2599539" "3479947" 1.5 ""
"F_CANDD_PRPS_INTR" "Candida parapsilosis intermedia" "synonym" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "parapsilosis" "intermedia" "subspecies" "Kreger-van Rij et al." "GBIF" "3480258" "2599539" "3479947" 1.5 "" "F_CANDD_PRPS_INTR" "Candida parapsilosis intermedia" "synonym" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "parapsilosis" "intermedia" "subspecies" "Kreger-van Rij et al." "GBIF" "3480258" "2599539" "3479947" 1.5 ""
"F_CANDD_PRPS_PRPS" "Candida parapsilosis parapsilosis" "synonym" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "parapsilosis" "parapsilosis" "subspecies" "GBIF" "11331780" "2599539" "2599539" 1.5 "" "F_CANDD_PRPS_PRPS" "Candida parapsilosis parapsilosis" "synonym" "Fungi" "Ascomycota" "Saccharomycetes" "Saccharomycetales" "Debaryomycetaceae" "Candida" "parapsilosis" "parapsilosis" "subspecies" "GBIF" "11331780" "2599539" "2599539" 1.5 ""
@ -11190,6 +11195,7 @@
"B_CTRBC" "Citrobacter" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Citrobacter" "" "" "genus" "Werkman et al., 1932" "facultative anaerobe" "LPSN" "515376" "482" "11150190" "11158430" 1 "1089501000112101,75972000" "B_CTRBC" "Citrobacter" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Citrobacter" "" "" "genus" "Werkman et al., 1932" "facultative anaerobe" "LPSN" "515376" "482" "11150190" "11158430" 1 "1089501000112101,75972000"
"B_CTRBC_AMLNT" "Citrobacter amalonatica" "synonym" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Citrobacter" "amalonatica" "" "species" "Young et al., 1971" "aerobe" "GBIF" "5427576" "11150190" "3221795" 1 "" "B_CTRBC_AMLNT" "Citrobacter amalonatica" "synonym" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Citrobacter" "amalonatica" "" "species" "Young et al., 1971" "aerobe" "GBIF" "5427576" "11150190" "3221795" 1 ""
"B_CTRBC_AMLN" "Citrobacter amalonaticus" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Citrobacter" "amalonaticus" "" "species" "Brenner et al., 1982" "aerobe" "LPSN" "774743" "515376" "3221795" "11150190" 1 "1089101000112105,55744003" "B_CTRBC_AMLN" "Citrobacter amalonaticus" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Citrobacter" "amalonaticus" "" "species" "Brenner et al., 1982" "aerobe" "LPSN" "774743" "515376" "3221795" "11150190" 1 "1089101000112105,55744003"
"B_CTRBC_AMLN-C" "Citrobacter amalonaticus complex" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Citrobacter" "amalonaticus complex" "" "species group" "aerobe" "manually added" "515376" "11150190" 1 ""
"B_CTRBC_BTTR" "Citrobacter bitternis" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Citrobacter" "bitternis" "" "species" "Ko et al., 2015" "likely facultative anaerobe" "GBIF" "11113073" "11150190" 1.5 "" "B_CTRBC_BTTR" "Citrobacter bitternis" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Citrobacter" "bitternis" "" "species" "Ko et al., 2015" "likely facultative anaerobe" "GBIF" "11113073" "11150190" 1.5 ""
"B_CTRBC_BRAK" "Citrobacter braakii" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Citrobacter" "braakii" "" "species" "Brenner et al., 1993" "aerobe" "LPSN" "774744" "515376" "3221791" "11150190" 1 "1089301000112107,114262000" "B_CTRBC_BRAK" "Citrobacter braakii" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Citrobacter" "braakii" "" "species" "Brenner et al., 1993" "aerobe" "LPSN" "774744" "515376" "3221791" "11150190" 1 "1089301000112107,114262000"
"B_CTRBC_CRON" "Citrobacter cronae" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Citrobacter" "cronae" "" "species" "Oberhettinger et al., 2020" "likely facultative anaerobe" "LPSN" "7473" "515376" "11248376" "11150190" "3221797" 1 "" "B_CTRBC_CRON" "Citrobacter cronae" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Citrobacter" "cronae" "" "species" "Oberhettinger et al., 2020" "likely facultative anaerobe" "LPSN" "7473" "515376" "11248376" "11150190" "3221797" 1 ""
@ -16134,6 +16140,7 @@
"B_ENTRBC_CHND" "Enterobacter chuandaensis" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Enterobacter" "chuandaensis" "" "species" "Wu et al., 2019" "facultative anaerobe" "LPSN" "800158" "515587" "10745032" "11204930" 1.5 "" "B_ENTRBC_CHND" "Enterobacter chuandaensis" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Enterobacter" "chuandaensis" "" "species" "Wu et al., 2019" "facultative anaerobe" "LPSN" "800158" "515587" "10745032" "11204930" 1.5 ""
"B_ENTRBC_CLOC" "Enterobacter cloacae" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Enterobacter" "cloacae" "" "species" "Hormaeche et al., 1960" "aerobe" "LPSN" "775933" "515587" "11234351" "11204930" 1 "714007005,737529000,14385002,721910001,714317005" "B_ENTRBC_CLOC" "Enterobacter cloacae" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Enterobacter" "cloacae" "" "species" "Hormaeche et al., 1960" "aerobe" "LPSN" "775933" "515587" "11234351" "11204930" 1 "714007005,737529000,14385002,721910001,714317005"
"B_ENTRBC_CLOC_CLOC" "Enterobacter cloacae cloacae" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Enterobacter" "cloacae" "cloacae" "subspecies" "Hoffmann et al., 2005" "LPSN" "775934" "775933" "7234533" "11234351" 1 "" "B_ENTRBC_CLOC_CLOC" "Enterobacter cloacae cloacae" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Enterobacter" "cloacae" "cloacae" "subspecies" "Hoffmann et al., 2005" "LPSN" "775934" "775933" "7234533" "11234351" 1 ""
"B_ENTRBC_CLOC-C" "Enterobacter cloacae complex" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Enterobacter" "cloacae complex" "" "species group" "aerobe" "manually added" "515587" "11204930" 1 ""
"B_ENTRBC_CLOC_DSSL" "Enterobacter cloacae dissolvens" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Enterobacter" "cloacae" "dissolvens" "subspecies" "Hoffmann et al., 2005" "aerobe" "LPSN" "775935" "775933" "3221982" "11234351" 1 "" "B_ENTRBC_CLOC_DSSL" "Enterobacter cloacae dissolvens" "accepted" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Enterobacter" "cloacae" "dissolvens" "subspecies" "Hoffmann et al., 2005" "aerobe" "LPSN" "775935" "775933" "3221982" "11234351" 1 ""
"B_ENTRBC_COWN" "Enterobacter cowanii" "synonym" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Enterobacter" "cowanii" "" "species" "Inoue et al., 2001" "aerobe" "LPSN" "775936" "515587" "791223" 1 "" "B_ENTRBC_COWN" "Enterobacter cowanii" "synonym" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Enterobacter" "cowanii" "" "species" "Inoue et al., 2001" "aerobe" "LPSN" "775936" "515587" "791223" 1 ""
"B_ENTRBC_DSSL" "Enterobacter dissolvens" "synonym" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Enterobacter" "dissolvens" "" "species" "Brenner et al., 1988" "aerobe" "LPSN" "775937" "515587" "775935" "3221983" "11204930" "3221982" 1.5 "" "B_ENTRBC_DSSL" "Enterobacter dissolvens" "synonym" "Bacteria" "Pseudomonadota" "Gammaproteobacteria" "Enterobacterales" "Enterobacteriaceae" "Enterobacter" "dissolvens" "" "species" "Brenner et al., 1988" "aerobe" "LPSN" "775937" "515587" "775935" "3221983" "11204930" "3221982" 1.5 ""

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@ -1,11 +1,11 @@
# ==================================================================== # # ==================================================================== #
# TITLE # # TITLE: #
# AMR: An R Package for Working with Antimicrobial Resistance Data # # AMR: An R Package for Working with Antimicrobial Resistance Data #
# # # #
# SOURCE # # SOURCE CODE: #
# https://github.com/msberends/AMR # # https://github.com/msberends/AMR #
# # # #
# CITE AS # # PLEASE CITE THIS SOFTWARE AS: #
# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C # # Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
# (2022). AMR: An R Package for Working with Antimicrobial Resistance # # (2022). AMR: An R Package for Working with Antimicrobial Resistance #
# Data. Journal of Statistical Software, 104(3), 1-31. # # Data. Journal of Statistical Software, 104(3), 1-31. #

6
data-raw/read_EUCAST.R
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@ -1,11 +1,11 @@
# ==================================================================== # # ==================================================================== #
# TITLE # # TITLE: #
# AMR: An R Package for Working with Antimicrobial Resistance Data # # AMR: An R Package for Working with Antimicrobial Resistance Data #
# # # #
# SOURCE # # SOURCE CODE: #
# https://github.com/msberends/AMR # # https://github.com/msberends/AMR #
# # # #
# CITE AS # # PLEASE CITE THIS SOFTWARE AS: #
# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C # # Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
# (2022). AMR: An R Package for Working with Antimicrobial Resistance # # (2022). AMR: An R Package for Working with Antimicrobial Resistance #
# Data. Journal of Statistical Software, 104(3), 1-31. # # Data. Journal of Statistical Software, 104(3), 1-31. #

6
data-raw/reproduction_of_antibiotics.R
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@ -1,11 +1,11 @@
# ==================================================================== # # ==================================================================== #
# TITLE # # TITLE: #
# AMR: An R Package for Working with Antimicrobial Resistance Data # # AMR: An R Package for Working with Antimicrobial Resistance Data #
# # # #
# SOURCE # # SOURCE CODE: #
# https://github.com/msberends/AMR # # https://github.com/msberends/AMR #
# # # #
# CITE AS # # PLEASE CITE THIS SOFTWARE AS: #
# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C # # Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
# (2022). AMR: An R Package for Working with Antimicrobial Resistance # # (2022). AMR: An R Package for Working with Antimicrobial Resistance #
# Data. Journal of Statistical Software, 104(3), 1-31. # # Data. Journal of Statistical Software, 104(3), 1-31. #

6
data-raw/reproduction_of_antivirals.R
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@ -1,11 +1,11 @@
# ==================================================================== # # ==================================================================== #
# TITLE # # TITLE: #
# AMR: An R Package for Working with Antimicrobial Resistance Data # # AMR: An R Package for Working with Antimicrobial Resistance Data #
# # # #
# SOURCE # # SOURCE CODE: #
# https://github.com/msberends/AMR # # https://github.com/msberends/AMR #
# # # #
# CITE AS # # PLEASE CITE THIS SOFTWARE AS: #
# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C # # Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
# (2022). AMR: An R Package for Working with Antimicrobial Resistance # # (2022). AMR: An R Package for Working with Antimicrobial Resistance #
# Data. Journal of Statistical Software, 104(3), 1-31. # # Data. Journal of Statistical Software, 104(3), 1-31. #

307
data-raw/reproduction_of_clinical_breakpoints.R
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@ -1,11 +1,11 @@
# ==================================================================== # # ==================================================================== #
# TITLE # # TITLE: #
# AMR: An R Package for Working with Antimicrobial Resistance Data # # AMR: An R Package for Working with Antimicrobial Resistance Data #
# # # #
# SOURCE # # SOURCE CODE: #
# https://github.com/msberends/AMR # # https://github.com/msberends/AMR #
# # # #
# CITE AS # # PLEASE CITE THIS SOFTWARE AS: #
# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C # # Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
# (2022). AMR: An R Package for Working with Antimicrobial Resistance # # (2022). AMR: An R Package for Working with Antimicrobial Resistance #
# Data. Journal of Statistical Software, 104(3), 1-31. # # Data. Journal of Statistical Software, 104(3), 1-31. #
@ -27,7 +27,7 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ # # how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== # # ==================================================================== #
# This script runs in under a minute and renews all guidelines of CLSI and EUCAST! # This script runs in 20-30 minutes and renews all guidelines of CLSI and EUCAST!
# Run it with source("data-raw/reproduction_of_clinical_breakpoints.R") # Run it with source("data-raw/reproduction_of_clinical_breakpoints.R")
library(dplyr) library(dplyr)
@ -39,40 +39,55 @@ devtools::load_all()
# and copy the folder C:\WHONET\Resources to the data-raw/WHONET/ folder # and copy the folder C:\WHONET\Resources to the data-raw/WHONET/ folder
# (for ASIARS-Net update, also copy C:\WHONET\Codes to the data-raw/WHONET/ folder) # (for ASIARS-Net update, also copy C:\WHONET\Codes to the data-raw/WHONET/ folder)
# READ DATA ----
# MICROORGANISMS WHONET CODES ----
whonet_organisms <- read_tsv("data-raw/WHONET/Resources/Organisms.txt", na = c("", "NA", "-"), show_col_types = FALSE) %>% whonet_organisms <- read_tsv("data-raw/WHONET/Resources/Organisms.txt", na = c("", "NA", "-"), show_col_types = FALSE) %>%
# remove old taxonomic names # remove old taxonomic names
filter(TAXONOMIC_STATUS == "C") %>% filter(TAXONOMIC_STATUS == "C") %>%
transmute(ORGANISM_CODE = tolower(WHONET_ORG_CODE), ORGANISM) %>% mutate(ORGANISM_CODE = toupper(WHONET_ORG_CODE))
mutate(
# what's wrong here? all these are only in the table on subspecies level (where species == subspecies), not on species level whonet_breakpoints <- read_tsv("data-raw/WHONET/Resources/Breakpoints.txt", na = c("", "NA", "-"),
ORGANISM = if_else(ORGANISM_CODE == "sau", "Staphylococcus aureus", ORGANISM), show_col_types = FALSE, guess_max = Inf) %>%
ORGANISM = if_else(ORGANISM_CODE == "pam", "Pasteurella multocida", ORGANISM), filter(GUIDELINES %in% c("CLSI", "EUCAST"))
ORGANISM = if_else(ORGANISM_CODE == "kpn", "Klebsiella pneumoniae", ORGANISM),
ORGANISM = if_else(ORGANISM_CODE == "caj", "Campylobacter jejuni", ORGANISM), whonet_antibiotics <- read_tsv("data-raw/WHONET/Resources/Antibiotics.txt", na = c("", "NA", "-"), show_col_types = FALSE) %>%
ORGANISM = if_else(ORGANISM_CODE == "mmo", "Morganella morganii", ORGANISM), arrange(WHONET_ABX_CODE) %>%
ORGANISM = if_else(ORGANISM_CODE == "sap", "Staphylococcus saprophyticus", ORGANISM), distinct(WHONET_ABX_CODE, .keep_all = TRUE)
ORGANISM = if_else(ORGANISM_CODE == "fne", "Fusobacterium necrophorum", ORGANISM),
ORGANISM = if_else(ORGANISM_CODE == "fnu", "Fusobacterium nucleatum", ORGANISM), # MICROORGANISMS WHONET CODES ----
ORGANISM = if_else(ORGANISM_CODE == "sdy", "Streptococcus dysgalactiae", ORGANISM),
ORGANISM = if_else(ORGANISM_CODE == "axy", "Achromobacter xylosoxidans", ORGANISM),
# and this one was called Issatchenkia orientalis, but it should be:
ORGANISM = if_else(ORGANISM_CODE == "ckr", "Candida krusei", ORGANISM)
)
# add some general codes
whonet_organisms <- whonet_organisms %>% whonet_organisms <- whonet_organisms %>%
bind_rows(data.frame( select(ORGANISM_CODE, ORGANISM, SPECIES_GROUP, GBIF_TAXON_ID) %>%
ORGANISM_CODE = c("ebc", "cof"), mutate(
ORGANISM = c("Enterobacterales", "Campylobacter") # this one was called Issatchenkia orientalis, but it should be:
)) ORGANISM = if_else(ORGANISM_CODE == "ckr", "Candida krusei", ORGANISM)
) %>%
# try to match on GBIF identifier
left_join(microorganisms %>% distinct(mo, gbif, status) %>% filter(!is.na(gbif)), by = c("GBIF_TAXON_ID" = "gbif")) %>%
# remove duplicates
arrange(ORGANISM_CODE, GBIF_TAXON_ID, status) %>%
distinct(ORGANISM_CODE, .keep_all = TRUE) %>%
# add Enterobacterales, which is a subkingdom code in their data
bind_rows(data.frame(ORGANISM_CODE = "ebc", ORGANISM = "Enterobacterales", mo = as.mo("Enterobacterales"))) %>%
arrange(ORGANISM)
# check non-existing species groups in the microorganisms table
complexes <- whonet_organisms %>%
filter(ORGANISM %like% " (group|complex)$" & toupper(SPECIES_GROUP) == toupper(ORGANISM_CODE)) %>%
mutate(mo = as.mo(ORGANISM, minimum_matching_score = 0.6, keep_synonyms = TRUE)) %>%
mutate(mo_new = paste0(mo, "-C"))
complexes[which(!complexes$mo_new %in% AMR::microorganisms$mo), ]
## Add new WHO codes to microorganisms.codes ----
matched <- whonet_organisms %>% filter(!is.na(mo))
unmatched <- whonet_organisms %>% filter(is.na(mo))
whonet_organisms.bak <- whonet_organisms
# generate the mo codes and add their names # generate the mo codes and add their names
whonet_organisms <- whonet_organisms.bak %>% message("Getting MO codes for WHONET input...")
mutate(mo = as.mo(gsub("(sero[a-z]*| complex| nontypable| non[-][a-zA-Z]+|var[.]| not .*|sp[.],.*|, .*variant.*|, .*toxin.*|, microaer.*| beta-haem[.])", "", ORGANISM), unmatched <- unmatched %>%
mutate(mo = as.mo(gsub("(sero[a-z]*| complex| group| nontypable| non[-][a-zA-Z]+|var[.]| not .*|sp[.],.*|, .*variant.*|, .*toxin.*|, microaer.*| beta-haem[.])", "", ORGANISM),
minimum_matching_score = 0.6, minimum_matching_score = 0.6,
keep_synonyms = TRUE, keep_synonyms = TRUE,
language = "en"), language = "en"),
@ -84,19 +99,48 @@ whonet_organisms <- whonet_organisms.bak %>%
keep_synonyms = TRUE, keep_synonyms = TRUE,
language = "en")) language = "en"))
# check if coercion at least resembles the first part (genus) # check if coercion at least resembles the first part (genus)
new_mo_codes <- whonet_organisms %>% unmatched <- unmatched %>%
mutate( mutate(
first_part = sapply(ORGANISM, function(x) strsplit(gsub("[^a-zA-Z _-]+", "", x), " ")[[1]][1], USE.NAMES = FALSE), first_part = sapply(ORGANISM, function(x) strsplit(gsub("[^a-zA-Z _-]+", "", x), " ")[[1]][1], USE.NAMES = FALSE),
keep = mo_name %like_case% first_part | ORGANISM %like% "Gram " | ORGANISM == "Other" | ORGANISM %like% "anaerobic") %>% keep = mo_name %like_case% first_part | ORGANISM %like% "Gram " | ORGANISM == "Other" | ORGANISM %like% "anaerobic") %>%
filter(keep == TRUE) %>% filter(keep == TRUE)
transmute(code = toupper(ORGANISM_CODE),
mo = mo) organisms <- matched %>% transmute(code = toupper(ORGANISM_CODE), group = SPECIES_GROUP, mo) %>%
bind_rows(unmatched %>% transmute(code = toupper(ORGANISM_CODE), group = SPECIES_GROUP, mo)) %>%
mutate(name = mo_name(mo, keep_synonyms = TRUE)) %>%
# remove the species groups themselves, we'll look the species within these groups later
filter(is.na(group) | code != group) %>%
arrange(code)
# some subspecies exist, while their upper species do not, add them as the species level:
subspp <- organisms %>%
filter(mo_species(mo, keep_synonyms = TRUE) == mo_subspecies(mo, keep_synonyms = TRUE) &
mo_species(mo, keep_synonyms = TRUE) != "" &
mo_genus(mo, keep_synonyms = TRUE) != "Salmonella") %>%
mutate(mo = as.mo(paste(mo_genus(mo, keep_synonyms = TRUE),
mo_species(mo, keep_synonyms = TRUE)),
keep_synonyms = TRUE),
name = mo_name(mo, keep_synonyms = TRUE))
organisms <- organisms %>%
filter(!code %in% subspp$code) %>%
bind_rows(subspp) %>%
arrange(code)
organism_groups <- organisms %>%
filter(!is.na(group)) %>%
arrange(group, name)
saveRDS(organism_groups, "data-raw/organism_groups.rds", version = 2)
#---
# AT THIS POINT, `organisms` is clean and all entries have an mo code
#---
# update microorganisms.codes with the latest WHONET codes # update microorganisms.codes with the latest WHONET codes
microorganisms.codes2 <- microorganisms.codes %>% microorganisms.codes2 <- microorganisms.codes %>%
# remove all old WHONET codes, whether we (in the end) keep them or not # remove all old WHONET codes, whether we (in the end) keep them or not
filter(!toupper(code) %in% toupper(new_mo_codes$code)) %>% filter(!toupper(code) %in% toupper(organisms$code) | toupper(code) %in% complexes$SPECIES_GROUP) %>%
# and add the new ones # and add the new ones
bind_rows(new_mo_codes) %>% bind_rows(organisms %>% filter(code != group) %>% select(code, mo)) %>%
arrange(code) arrange(code)
# new codes: # new codes:
microorganisms.codes2$code[which(!microorganisms.codes2$code %in% microorganisms.codes$code)] microorganisms.codes2$code[which(!microorganisms.codes2$code %in% microorganisms.codes$code)]
@ -104,31 +148,31 @@ mo_name(microorganisms.codes2$mo[which(!microorganisms.codes2$code %in% microorg
microorganisms.codes <- microorganisms.codes2 microorganisms.codes <- microorganisms.codes2
# Run this part to update ASIARS-Net: # Run this part to update ASIARS-Net:
# start # # start
asiarsnet <- read_tsv("data-raw/WHONET/Codes/ASIARS_Net_Organisms_ForwardLookup.txt") # asiarsnet <- read_tsv("data-raw/WHONET/Codes/ASIARS_Net_Organisms_ForwardLookup.txt")
asiarsnet <- asiarsnet %>% # asiarsnet <- asiarsnet %>%
mutate(WHONET_Code = toupper(WHONET_Code)) %>% # mutate(WHONET_Code = toupper(WHONET_Code)) %>%
left_join(whonet_organisms %>% mutate(WHONET_Code = toupper(ORGANISM_CODE))) %>% # left_join(whonet_organisms %>% mutate(WHONET_Code = toupper(ORGANISM_CODE))) %>%
mutate( # mutate(
mo1 = as.mo(ORGANISM_CODE), # mo1 = as.mo(ORGANISM_CODE),
mo2 = as.mo(ORGANISM) # mo2 = as.mo(ORGANISM)
) %>% # ) %>%
mutate(mo = if_else(mo2 == "UNKNOWN" | is.na(mo2), mo1, mo2)) %>% # mutate(mo = if_else(mo2 == "UNKNOWN" | is.na(mo2), mo1, mo2)) %>%
filter(!is.na(mo)) # filter(!is.na(mo))
insert1 <- asiarsnet %>% transmute(code = WHONET_Code, mo) # insert1 <- asiarsnet %>% transmute(code = WHONET_Code, mo)
insert2 <- asiarsnet %>% transmute(code = as.character(ASIARS_Net_Code), mo) # insert2 <- asiarsnet %>% transmute(code = as.character(ASIARS_Net_Code), mo)
# these will be updated # # these will be updated
bind_rows(insert1, insert2) %>% # bind_rows(insert1, insert2) %>%
rename(mo_new = mo) %>% # rename(mo_new = mo) %>%
left_join(microorganisms.codes) %>% # left_join(microorganisms.codes) %>%
filter(mo != mo_new) # filter(mo != mo_new)
microorganisms.codes <- microorganisms.codes %>% # microorganisms.codes <- microorganisms.codes %>%
filter(!code %in% c(insert1$code, insert2$code)) %>% # filter(!code %in% c(insert1$code, insert2$code)) %>%
bind_rows(insert1, insert2) %>% # bind_rows(insert1, insert2) %>%
arrange(code) # arrange(code)
# end # # end
# save to package ## Save to package ----
usethis::use_data(microorganisms.codes, overwrite = TRUE, compress = "xz", version = 2) usethis::use_data(microorganisms.codes, overwrite = TRUE, compress = "xz", version = 2)
rm(microorganisms.codes) rm(microorganisms.codes)
devtools::load_all() devtools::load_all()
@ -137,11 +181,11 @@ devtools::load_all()
# BREAKPOINTS ---- # BREAKPOINTS ----
# now that we have the right MO codes, get the breakpoints and convert them # now that we have the right MO codes, get the breakpoints and convert them
whonet_breakpoints <- read_tsv("data-raw/WHONET/Resources/Breakpoints.txt", na = c("", "NA", "-"), show_col_types = FALSE) %>%
filter(BREAKPOINT_TYPE == "Human", GUIDELINES %in% c("CLSI", "EUCAST")) whonet_breakpoints %>%
whonet_antibiotics <- read_tsv("data-raw/WHONET/Resources/Antibiotics.txt", na = c("", "NA", "-"), show_col_types = FALSE) %>% count(GUIDELINES, BREAKPOINT_TYPE) %>%
arrange(WHONET_ABX_CODE) %>% pivot_wider(names_from = BREAKPOINT_TYPE, values_from = n) %>%
distinct(WHONET_ABX_CODE, .keep_all = TRUE) janitor::adorn_totals(where = c("row", "col"))
breakpoints <- whonet_breakpoints %>% breakpoints <- whonet_breakpoints %>%
mutate(code = toupper(ORGANISM_CODE)) %>% mutate(code = toupper(ORGANISM_CODE)) %>%
@ -151,13 +195,14 @@ breakpoints <- whonet_breakpoints %>%
mo = rep(as.mo("UNKNOWN"), 2)))) mo = rep(as.mo("UNKNOWN"), 2))))
# these ones lack an MO name, they cannot be used: # these ones lack an MO name, they cannot be used:
unknown <- breakpoints %>% unknown <- breakpoints %>%
filter(is.na(mo)) %>% filter(is.na(mo) & !ORGANISM_CODE %in% organism_groups$group) %>%
pull(code) %>% pull(code) %>%
unique() unique()
breakpoints %>% breakpoints %>%
filter(code %in% unknown) filter(code %in% unknown) %>%
count(GUIDELINES, YEAR, ORGANISM_CODE, BREAKPOINT_TYPE, sort = TRUE)
breakpoints <- breakpoints %>% breakpoints <- breakpoints %>%
filter(!is.na(mo)) filter(!is.na(mo) | ORGANISM_CODE %in% organism_groups$group)
# and these ones have unknown antibiotics according to WHONET itself: # and these ones have unknown antibiotics according to WHONET itself:
breakpoints %>% breakpoints %>%
@ -168,21 +213,48 @@ breakpoints %>%
filter(!WHONET_ABX_CODE %in% whonet_antibiotics$WHONET_ABX_CODE) %>% filter(!WHONET_ABX_CODE %in% whonet_antibiotics$WHONET_ABX_CODE) %>%
pull(WHONET_ABX_CODE) %>% pull(WHONET_ABX_CODE) %>%
unique() unique()
# we cannot use them
# breakpoints <- breakpoints %>%
# filter(WHONET_ABX_CODE %in% whonet_antibiotics$WHONET_ABX_CODE)
# now check with our own antibiotics
breakpoints %>%
filter(!toupper(WHONET_ABX_CODE) %in% antibiotics$ab) %>%
pull(WHONET_ABX_CODE) %>%
unique()
# they are at the moment all old codes that have right replacements in `antibiotics`, so we can use as.ab() # they are at the moment all old codes that have right replacements in `antibiotics`, so we can use as.ab()
## Extend species groups ----
message("Extending breakpoints table on species groups...")
# get the species groups, they must be converted to rules per-species and added
breakpoints.bak <- breakpoints
spp_groups <- breakpoints %>% filter(ORGANISM_CODE_TYPE == "SPECIES_GROUP")
p <- progress_ticker(nrow(spp_groups))
for (i in seq_len(nrow(spp_groups))) {
p$tick()
mos <- organism_groups %>% filter(group == spp_groups[i, "ORGANISM_CODE", drop = TRUE]) %>% pull(mo)
for (m in mos) {
breakpoints <- breakpoints %>%
bind_rows(spp_groups %>%
slice(i) %>%
mutate(mo = m))
}
}
close(p)
# extend all group A and B streptococci
breakpoints_new <- breakpoints_new %>%
bind_rows(breakpoints_new %>%
filter(mo == as.mo("Streptococcus Group A")) %>%
mutate(mo = as.mo("Streptococcus pyogenes"))) %>%
bind_rows(breakpoints_new %>%
filter(mo == as.mo("Streptococcus Group B")) %>%
mutate(mo = as.mo("Streptococcus agalactiae")))
# remove duplicates again for CoNS/CoPS/GBS and arrange
breakpoints_new <- breakpoints_new %>%
mutate(mo = as.mo(mo, keep_synonyms = TRUE)) %>%
distinct(guideline, ab, mo, method, site, .keep_all = TRUE) %>%
arrange(desc(guideline), ab, mo, method)
## Build new breakpoints table ----
breakpoints_new <- breakpoints %>% breakpoints_new <- breakpoints %>%
# only last available 10 years filter(!is.na(WHONET_ABX_CODE)) %>%
# filter(YEAR > max(YEAR) - 10) %>%
transmute( transmute(
guideline = paste(GUIDELINES, YEAR), guideline = paste(GUIDELINES, YEAR),
type = ifelse(BREAKPOINT_TYPE == "ECOFF", "ECOFF", tolower(BREAKPOINT_TYPE)),
method = TEST_METHOD, method = TEST_METHOD,
site = SITE_OF_INFECTION, site = SITE_OF_INFECTION,
mo, mo,
@ -196,10 +268,10 @@ breakpoints_new <- breakpoints %>%
TRUE ~ 6 TRUE ~ 6
), ),
ab = as.ab(WHONET_ABX_CODE), ab = as.ab(WHONET_ABX_CODE),
ref_tbl = REFERENCE_TABLE, ref_tbl = ifelse(type == "ECOFF" & is.na(REFERENCE_TABLE), "ECOFF", REFERENCE_TABLE),
disk_dose = POTENCY, disk_dose = POTENCY,
breakpoint_S = S, breakpoint_S = ifelse(type == "ECOFF" & is.na(S) & !is.na(ECV_ECOFF), ECV_ECOFF, S),
breakpoint_R = R, breakpoint_R = ifelse(type == "ECOFF" & is.na(R) & !is.na(ECV_ECOFF), ECV_ECOFF, R),
uti = ifelse(is.na(site), FALSE, gsub(".*(UTI|urinary|urine).*", "UTI", site) == "UTI") uti = ifelse(is.na(site), FALSE, gsub(".*(UTI|urinary|urine).*", "UTI", site) == "UTI")
) %>% ) %>%
# Greek symbols and EM dash symbols are not allowed by CRAN, so replace them with ASCII: # Greek symbols and EM dash symbols are not allowed by CRAN, so replace them with ASCII:
@ -213,7 +285,7 @@ breakpoints_new <- breakpoints %>%
# check the strange duplicates # check the strange duplicates
breakpoints_new %>% breakpoints_new %>%
mutate(id = paste(guideline, ab, mo, method, site)) %>% mutate(id = paste(guideline, type, ab, mo, method, site)) %>%
filter(id %in% .$id[which(duplicated(id))]) filter(id %in% .$id[which(duplicated(id))])
# remove duplicates # remove duplicates
breakpoints_new <- breakpoints_new %>% breakpoints_new <- breakpoints_new %>%
@ -272,74 +344,7 @@ clinical_breakpoints %>% filter(guideline == "EUCAST 2022", ab == "AMC", mo == "
dim(breakpoints_new) dim(breakpoints_new)
dim(clinical_breakpoints) dim(clinical_breakpoints)
# ECOFFs ---- # SAVE TO PACKAGE ----
# ECOFF = Epidemiological Cut-Off
whonet_ecoff <- read_tsv("data-raw/WHONET/Resources/Breakpoints.txt", na = c("", "NA", "-"), show_col_types = FALSE) %>%
filter(BREAKPOINT_TYPE == "ECOFF", GUIDELINES %in% c("CLSI", "EUCAST"))
ecoff <- whonet_ecoff %>%
filter(!ORGANISM_CODE %in% c("clu", "BFX", "PFX", "kma", "cdh")) %>%
transmute(guideline = paste(GUIDELINES, YEAR),
mo = as.mo(ORGANISM_CODE, keep_synonyms = TRUE),
ab = as.ab(WHONET_ABX_CODE),
method = TEST_METHOD,
ecoff = as.double(ECV_ECOFF)) %>%
filter(!is.na(ecoff)) %>%
distinct()
# join to breakpoints
breakpoints_new <- breakpoints_new %>%
bind_rows(breakpoints_new %>%
right_join(ecoff, by = c("guideline", "mo", "ab", "method"))) %>%
mutate(ref_tbl = ifelse(is.na(ref_tbl), "ECOFF", ref_tbl)) %>%
distinct(guideline, ab, mo, method, site, .keep_all = TRUE) %>%
arrange(desc(guideline), ab, mo, method) %>%
mutate(rank_index = case_when(
is.na(mo_rank(mo, keep_synonyms = TRUE)) ~ 6, # for UNKNOWN, B_GRAMN, B_ANAER, B_ANAER-NEG, etc.
mo_rank(mo, keep_synonyms = TRUE) %like% "(infra|sub)" ~ 1,
mo_rank(mo, keep_synonyms = TRUE) == "species" ~ 2,
mo_rank(mo, keep_synonyms = TRUE) == "genus" ~ 3,
mo_rank(mo, keep_synonyms = TRUE) == "family" ~ 4,
mo_rank(mo, keep_synonyms = TRUE) == "order" ~ 5,
TRUE ~ 6
)) %>%
mutate(uti = ifelse(is.na(uti), FALSE, uti)) %>%
relocate(ecoff, .after = breakpoint_R)
breakpoints_new.bak <- mutate(uti = ifelse(is.na(uti), FALSE, uti), .after = ecoff)
# EXTEND CoNS/CoPS/GAS/GBS ----
# extend all coagulase-postive/-negative staphylococci
CoNS <- breakpoints_new %>% filter(mo == as.mo("CoNS"))
for (m in MO_CONS[mo_subspecies(MO_CONS, keep_synonyms = TRUE) == ""]) {
breakpoints_new <- breakpoints_new %>%
bind_rows(CoNS %>%
mutate(mo = m))
}
CoPS <- breakpoints_new %>% filter(mo == as.mo("CoPS"))
for (m in MO_COPS[mo_subspecies(MO_COPS, keep_synonyms = TRUE) == ""]) {
breakpoints_new <- breakpoints_new %>%
bind_rows(CoPS %>%
mutate(mo = m))
}
# do the same for group A and B streptococci
breakpoints_new <- breakpoints_new %>%
bind_rows(breakpoints_new %>%
filter(mo == as.mo("Streptococcus Group A")) %>%
mutate(mo = as.mo("Streptococcus pyogenes"))) %>%
bind_rows(breakpoints_new %>%
filter(mo == as.mo("Streptococcus Group B")) %>%
mutate(mo = as.mo("Streptococcus agalactiae")))
# remove duplicates again for CoNS/CoPS/GBS and arrange
breakpoints_new <- breakpoints_new %>%
mutate(mo = as.mo(mo, keep_synonyms = TRUE)) %>%
distinct(guideline, ab, mo, method, site, .keep_all = TRUE) %>%
arrange(desc(guideline), ab, mo, method)
# Save to package ----
clinical_breakpoints <- breakpoints_new clinical_breakpoints <- breakpoints_new
usethis::use_data(clinical_breakpoints, overwrite = TRUE, compress = "xz", version = 2) usethis::use_data(clinical_breakpoints, overwrite = TRUE, compress = "xz", version = 2)

6
data-raw/reproduction_of_dosage.R
View File

@ -1,11 +1,11 @@
# ==================================================================== # # ==================================================================== #
# TITLE # # TITLE: #
# AMR: An R Package for Working with Antimicrobial Resistance Data # # AMR: An R Package for Working with Antimicrobial Resistance Data #
# # # #
# SOURCE # # SOURCE CODE: #
# https://github.com/msberends/AMR # # https://github.com/msberends/AMR #
# # # #
# CITE AS # # PLEASE CITE THIS SOFTWARE AS: #
# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C # # Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
# (2022). AMR: An R Package for Working with Antimicrobial Resistance # # (2022). AMR: An R Package for Working with Antimicrobial Resistance #
# Data. Journal of Statistical Software, 104(3), 1-31. # # Data. Journal of Statistical Software, 104(3), 1-31. #

6
data-raw/reproduction_of_example_isolates_unclean.R
View File

@ -1,11 +1,11 @@
# ==================================================================== # # ==================================================================== #
# TITLE # # TITLE: #
# AMR: An R Package for Working with Antimicrobial Resistance Data # # AMR: An R Package for Working with Antimicrobial Resistance Data #
# # # #
# SOURCE # # SOURCE CODE: #
# https://github.com/msberends/AMR # # https://github.com/msberends/AMR #
# # # #
# CITE AS # # PLEASE CITE THIS SOFTWARE AS: #
# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C # # Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
# (2022). AMR: An R Package for Working with Antimicrobial Resistance # # (2022). AMR: An R Package for Working with Antimicrobial Resistance #
# Data. Journal of Statistical Software, 104(3), 1-31. # # Data. Journal of Statistical Software, 104(3), 1-31. #

6
data-raw/reproduction_of_intrinsic_resistant.R
View File

@ -1,11 +1,11 @@
# ==================================================================== # # ==================================================================== #
# TITLE # # TITLE: #
# AMR: An R Package for Working with Antimicrobial Resistance Data # # AMR: An R Package for Working with Antimicrobial Resistance Data #
# # # #
# SOURCE # # SOURCE CODE: #
# https://github.com/msberends/AMR # # https://github.com/msberends/AMR #
# # # #
# CITE AS # # PLEASE CITE THIS SOFTWARE AS: #
# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C # # Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
# (2022). AMR: An R Package for Working with Antimicrobial Resistance # # (2022). AMR: An R Package for Working with Antimicrobial Resistance #
# Data. Journal of Statistical Software, 104(3), 1-31. # # Data. Journal of Statistical Software, 104(3), 1-31. #

6
data-raw/reproduction_of_microorganisms.R
View File

@ -1,11 +1,11 @@
# ==================================================================== # # ==================================================================== #
# TITLE # # TITLE: #
# AMR: An R Package for Working with Antimicrobial Resistance Data # # AMR: An R Package for Working with Antimicrobial Resistance Data #
# # # #
# SOURCE # # SOURCE CODE: #
# https://github.com/msberends/AMR # # https://github.com/msberends/AMR #
# # # #
# CITE AS # # PLEASE CITE THIS SOFTWARE AS: #
# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C # # Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
# (2022). AMR: An R Package for Working with Antimicrobial Resistance # # (2022). AMR: An R Package for Working with Antimicrobial Resistance #
# Data. Journal of Statistical Software, 104(3), 1-31. # # Data. Journal of Statistical Software, 104(3), 1-31. #

6
data-raw/salmonellae.R
View File

@ -1,11 +1,11 @@
# ==================================================================== # # ==================================================================== #
# TITLE # # TITLE: #
# AMR: An R Package for Working with Antimicrobial Resistance Data # # AMR: An R Package for Working with Antimicrobial Resistance Data #
# # # #
# SOURCE # # SOURCE CODE: #
# https://github.com/msberends/AMR # # https://github.com/msberends/AMR #
# # # #
# CITE AS # # PLEASE CITE THIS SOFTWARE AS: #
# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C # # Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
# (2022). AMR: An R Package for Working with Antimicrobial Resistance # # (2022). AMR: An R Package for Working with Antimicrobial Resistance #
# Data. Journal of Statistical Software, 104(3), 1-31. # # Data. Journal of Statistical Software, 104(3), 1-31. #

10
man/as.sir.Rd
View File

@ -43,7 +43,7 @@ is_sir_eligible(x, threshold = 0.05)
reference_data = AMR::clinical_breakpoints, reference_data = AMR::clinical_breakpoints,
include_screening = getOption("AMR_include_screening", FALSE), include_screening = getOption("AMR_include_screening", FALSE),
include_PKPD = getOption("AMR_include_PKPD", TRUE), include_PKPD = getOption("AMR_include_PKPD", TRUE),
ecoff = getOption("AMR_ecoff", FALSE), breakpoint_type = getOption("AMR_breakpoint_type", FALSE),
... ...
) )
@ -57,7 +57,7 @@ is_sir_eligible(x, threshold = 0.05)
reference_data = AMR::clinical_breakpoints, reference_data = AMR::clinical_breakpoints,
include_screening = getOption("AMR_include_screening", FALSE), include_screening = getOption("AMR_include_screening", FALSE),
include_PKPD = getOption("AMR_include_PKPD", TRUE), include_PKPD = getOption("AMR_include_PKPD", TRUE),
ecoff = getOption("AMR_ecoff", FALSE), breakpoint_type = getOption("AMR_breakpoint_type", FALSE),
... ...
) )
@ -72,7 +72,7 @@ is_sir_eligible(x, threshold = 0.05)
reference_data = AMR::clinical_breakpoints, reference_data = AMR::clinical_breakpoints,
include_screening = getOption("AMR_include_screening", FALSE), include_screening = getOption("AMR_include_screening", FALSE),
include_PKPD = getOption("AMR_include_PKPD", TRUE), include_PKPD = getOption("AMR_include_PKPD", TRUE),
ecoff = getOption("AMR_ecoff", FALSE) breakpoint_type = getOption("AMR_breakpoint_type", FALSE)
) )
sir_interpretation_history(clean = FALSE) sir_interpretation_history(clean = FALSE)
@ -102,7 +102,7 @@ sir_interpretation_history(clean = FALSE)
\item{include_PKPD}{a \link{logical} to indicate that PK/PD clinical breakpoints must be applied as a last resort - the default is \code{TRUE}. Can also be set with the \link[=AMR-options]{package option} \code{\link[=AMR-options]{AMR_include_PKPD}}.} \item{include_PKPD}{a \link{logical} to indicate that PK/PD clinical breakpoints must be applied as a last resort - the default is \code{TRUE}. Can also be set with the \link[=AMR-options]{package option} \code{\link[=AMR-options]{AMR_include_PKPD}}.}
\item{ecoff}{a \link{logical} to indicate that ECOFF (Epidemiological Cut-Off) values must be used \strong{instead} of other clinical breakpoints - the default is \code{FALSE}. Can also be set with the \link[=AMR-options]{package option} \code{\link[=AMR-options]{AMR_ecoff}}.} \item{breakpoint_type}{the type of breakpoints to use, either "". ECOFF stands for Epidemiological Cut-Off values. The default is \code{"human"}, which can also be set with the \link[=AMR-options]{package option} \code{\link[=AMR-options]{AMR_breakpoint_type}}.}
\item{col_mo}{column name of the names or codes of the microorganisms (see \code{\link[=as.mo]{as.mo()}}) - the default is the first column of class \code{\link{mo}}. Values will be coerced using \code{\link[=as.mo]{as.mo()}}.} \item{col_mo}{column name of the names or codes of the microorganisms (see \code{\link[=as.mo]{as.mo()}}) - the default is the first column of class \code{\link{mo}}. Values will be coerced using \code{\link[=as.mo]{as.mo()}}.}
@ -114,6 +114,8 @@ Ordered \link{factor} with new class \code{sir}
\description{ \description{
Interpret minimum inhibitory concentration (MIC) values and disk diffusion diameters according to EUCAST or CLSI, or clean up existing SIR values. This transforms the input to a new class \code{\link{sir}}, which is an ordered \link{factor} with levels \verb{S < I < R}. Interpret minimum inhibitory concentration (MIC) values and disk diffusion diameters according to EUCAST or CLSI, or clean up existing SIR values. This transforms the input to a new class \code{\link{sir}}, which is an ordered \link{factor} with levels \verb{S < I < R}.
Currently available \strong{breakpoint guidelines} are EUCAST 2011-2023 and CLSI 2011-2023, and available \strong{breakpoint types} are "".
All breakpoints used for interpretation are publicly available in the \link{clinical_breakpoints} data set. All breakpoints used for interpretation are publicly available in the \link{clinical_breakpoints} data set.
} }
\details{ \details{

4
man/microorganisms.Rd
View File

@ -3,9 +3,9 @@
\docType{data} \docType{data}
\name{microorganisms} \name{microorganisms}
\alias{microorganisms} \alias{microorganisms}
\title{Data Set with 52 151 Microorganisms} \title{Data Set with 52 158 Microorganisms}
\format{ \format{
A \link[tibble:tibble]{tibble} with 52 151 observations and 23 variables: A \link[tibble:tibble]{tibble} with 52 158 observations and 23 variables:
\itemize{ \itemize{
\item \code{mo}\cr ID of microorganism as used by this package \item \code{mo}\cr ID of microorganism as used by this package
\item \code{fullname}\cr Full name, like \code{"Escherichia coli"}. For the taxonomic ranks genus, species and subspecies, this is the 'pasted' text of genus, species, and subspecies. For all taxonomic ranks higher than genus, this is the name of the taxon. \item \code{fullname}\cr Full name, like \code{"Escherichia coli"}. For the taxonomic ranks genus, species and subspecies, this is the 'pasted' text of genus, species, and subspecies. For all taxonomic ranks higher than genus, this is the name of the taxon.

4
man/microorganisms.codes.Rd
View File

@ -3,9 +3,9 @@
\docType{data} \docType{data}
\name{microorganisms.codes} \name{microorganisms.codes}
\alias{microorganisms.codes} \alias{microorganisms.codes}
\title{Data Set with 4 942 Common Microorganism Codes} \title{Data Set with 4 946 Common Microorganism Codes}
\format{ \format{
A \link[tibble:tibble]{tibble} with 4 942 observations and 2 variables: A \link[tibble:tibble]{tibble} with 4 946 observations and 2 variables:
\itemize{ \itemize{
\item \code{code}\cr Commonly used code of a microorganism \item \code{code}\cr Commonly used code of a microorganism
\item \code{mo}\cr ID of the microorganism in the \link{microorganisms} data set \item \code{mo}\cr ID of the microorganism in the \link{microorganisms} data set