mirror of https://github.com/msberends/AMR.git
1129 lines
37 KiB
R
1129 lines
37 KiB
R
# ==================================================================== #
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# TITLE #
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# Antimicrobial Resistance (AMR) Data Analysis for R #
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# #
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# SOURCE #
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# https://github.com/msberends/AMR #
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# #
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# LICENCE #
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# (c) 2018-2022 Berends MS, Luz CF et al. #
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# Developed at the University of Groningen, the Netherlands, in #
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# collaboration with non-profit organisations Certe Medical #
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# Diagnostics & Advice, and University Medical Center Groningen. #
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# #
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# This R package is free software; you can freely use and distribute #
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# it for both personal and commercial purposes under the terms of the #
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# GNU General Public License version 2.0 (GNU GPL-2), as published by #
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# the Free Software Foundation. #
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# We created this package for both routine data analysis and academic #
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# research and it was publicly released in the hope that it will be #
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# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
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# #
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# Visit our website for the full manual and a complete tutorial about #
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# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
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# ==================================================================== #
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# Reproduction of the `microorganisms` data set
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# Data retrieved from the Catalogue of Life (CoL):
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# https://download.catalogueoflife.org/col/monthly/
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# (download latest dwca, such as https://download.catalogueoflife.org/col/monthly/2022-01-14_dwca.zip)
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# Data retrieved from the Global Biodiversity Information Facility (GBIF):
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# https://doi.org/10.15468/rffz4x
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#
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# And from the List of Prokaryotic names with Standing in Nomenclature (LPSN)
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# (register first) https://lpsn.dsmz.de/downloads
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# download the latest CSV file.
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library(dplyr)
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library(AMR)
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# also needed: data.table, httr, jsonlite, cleaner, stringr
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# unzip and extract taxa.txt (both around 1.5 GB, 3.7-3.9M rows) from Col and GBIF, then:
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data_col_raw <- data.table::fread("data-raw/taxon.tsv", quote = "")
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data_gbif <- data.table::fread("data-raw/taxa.txt", quote = "")
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# merge the two
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data_col <- data_gbif %>%
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rename(referenceID = identifier) %>%
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bind_rows(data_col_raw) %>%
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distinct(scientificName, kingdom, genus, specificEpithet, infraspecificEpithet, .keep_all = TRUE)
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rm(data_col_raw)
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rm(data_gbif)
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# read the data from the DSMZ API (around 19000 rows)
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dsmz_username <- ""
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dsmz_password <- ""
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GET_df <- function(url) {
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result <- httr::GET(url, httr::authenticate(dsmz_username, dsmz_password))
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httr::stop_for_status(result)
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result %>%
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httr::content(type = "text", encoding = "UTF-8") %>%
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jsonlite::fromJSON(flatten = TRUE)
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}
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dsmz_first <- GET_df("https://bacdive.dsmz.de/api/pnu/species?page=1&format=json")
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data_dsmz <- dsmz_first$results
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# this next process will take appr. `dsmz_first$count / 100 * 5 / 60` minutes
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for (i in 2:round((dsmz_first$count / 100) + 0.5)) {
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data_dsmz <<- rbind(
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data_dsmz,
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GET_df(paste0("https://bacdive.dsmz.de/api/pnu/species/?page=", i, "&format=json"))$results
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)
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cat(i, "-", AMR:::percentage(i / round((dsmz_first$count / 100) + 0.5)), "\n")
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}
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rm(dsmz_first)
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# the CoL data is over 3.7M rows:
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data_col %>% cleaner::freq(kingdom)
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# Item Count Percent Cum. Count Cum. Percent
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# --- ---------- ---------- -------- ----------- -------------
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# 1 Animalia 2,494,992 55.43% 2,494,992 55.43%
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# 2 Plantae 1,379,674 30.65% 3,874,666 86.08%
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# 3 Fungi 547,619 12.17% 4,422,285 98.24%
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# 4 Chromista 51,475 1.14% 4,473,760 99.39%
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# 5 Bacteria 14,442 0.32% 4,488,202 99.71%
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# 6 Protozoa 8,750 0.19% 4,496,952 99.90%
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# 7 Viruses 3,805 0.08% 4,500,757 99.99%
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# 8 Archaea 609 0.01% 4,501,366 100.00%
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# clean data_col
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data_col.bak <- data_col
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data_col_old <- data_col %>%
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# filter: has new accepted name
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filter(!is.na(acceptedNameUsageID)) %>%
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as_tibble() %>%
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transmute(
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fullname = trimws(stringr::str_replace(scientificName,
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pattern = stringr::fixed(scientificNameAuthorship),
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replacement = ""
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)),
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fullname_new = trimws(paste(
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ifelse(is.na(genus), "", genus),
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ifelse(is.na(specificEpithet), "", specificEpithet),
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ifelse(is.na(infraspecificEpithet), "", infraspecificEpithet)
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)),
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ref = scientificNameAuthorship,
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prevalence = NA_integer_
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)
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data_col <- data_col %>%
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# filter: has no new accepted name
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filter(is.na(acceptedNameUsageID)) %>%
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as_tibble() %>%
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transmute(
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fullname = "",
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kingdom,
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phylum,
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class,
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order,
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family,
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genus,
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species = specificEpithet,
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subspecies = infraspecificEpithet,
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rank = taxonRank,
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ref = scientificNameAuthorship,
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species_id = referenceID,
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source = "CoL"
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)
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# clean data_dsmz
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data_dsmz.bak <- data_dsmz
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data_dsmz_old <- data_dsmz %>%
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# filter: correct name is not NULL
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filter(!sapply(correct_name, is.null)) %>%
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as_tibble() %>%
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transmute(
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fullname = trimws(paste(
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ifelse(is.na(genus), "", genus),
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ifelse(is.na(species_epithet), "", species_epithet),
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ifelse(is.na(subspecies_epithet), "", subspecies_epithet)
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)),
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fullname_new = sapply(correct_name, function(x) x[2L]),
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ref = authors,
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prevalence = NA_integer_
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)
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data_dsmz <- data_dsmz %>%
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# filter: correct name is NULL
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filter(sapply(correct_name, is.null)) %>%
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as_tibble() %>%
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transmute(
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fullname = "",
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kingdom = regio,
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phylum,
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class = classis,
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# order = "", # does not contain order, will add later based on CoL
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family = familia,
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genus = ifelse(is.na(genus), "", genus),
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species = ifelse(is.na(species_epithet), "", species_epithet),
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subspecies = ifelse(is.na(subspecies_epithet), "", subspecies_epithet),
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rank = ifelse(species == "", "genus", "species"),
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ref = authors,
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species_id = as.character(pnu_no),
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source = "DSMZ"
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)
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# DSMZ only contains genus/(sub)species, try to find taxonomic properties based on genus and data_col
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ref_taxonomy <- data_col %>%
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filter(family %in% data_dsmz$family & family != "") %>%
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arrange(kingdom) %>%
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distinct(family, .keep_all = TRUE) %>%
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select(family, order)
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data_dsmz <- data_dsmz %>%
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left_join(ref_taxonomy, by = "family") # NAs will later become "(unknown ...)"
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# combine everything
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data_total <- data_col %>%
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bind_rows(data_dsmz)
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rm(data_col)
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rm(data_dsmz)
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rm(ref_taxonomy)
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rm(data_col.bak)
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rm(data_dsmz.bak)
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MOs <- data_total %>%
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filter(
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(
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# we only want all MICROorganisms and no viruses
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!kingdom %in% c("Animalia", "Plantae", "Viruses")
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# and not all fungi: Aspergillus, Candida, Trichphyton and Pneumocystis are the most important,
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# so only keep these orders from the fungi:
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& !(kingdom == "Fungi" &
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!order %in% c("Eurotiales", "Microascales", "Mucorales", "Saccharomycetales", "Schizosaccharomycetales", "Tremellales", "Onygenales", "Pneumocystales"))
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)
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# or the genus has to be one of the genera we found in our hospitals last decades (Northern Netherlands, 2002-2018)
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| genus %in% MO_PREVALENT_GENERA
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) %>%
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# really no Plantae (e.g. Dracunculus exist both as worm and as plant)
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filter(kingdom != "Plantae") %>%
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filter(!rank %in% c("kingdom", "phylum", "class", "order", "family", "genus"))
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# include all ranks other than species for the included species
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MOs <- MOs %>% bind_rows(data_total %>%
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filter((kingdom %in% MOs$kingdom & rank == "kingdom") |
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(phylum %in% MOs$phylum & rank == "phylum") |
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(class %in% MOs$class & rank == "class") |
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(order %in% MOs$order & rank == "order") |
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(family %in% MOs$family & rank == "family") |
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(genus %in% MOs$genus & rank == "genus")))
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get_author_year <- function(ref) {
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# Only keep first author, e.g. transform 'Smith, Jones, 2011' to 'Smith et al., 2011'
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authors2 <- iconv(ref, from = "UTF-8", to = "ASCII//TRANSLIT")
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# remove leading and trailing brackets
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authors2 <- gsub("^[(](.*)[)]$", "\\1", authors2)
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# only take part after brackets if there's a name
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authors2 <- ifelse(grepl(".*[)] [a-zA-Z]+.*", authors2),
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gsub(".*[)] (.*)", "\\1", authors2),
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authors2
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)
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# get year from last 4 digits
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lastyear <- as.integer(gsub(".*([0-9]{4})$", "\\1", authors2))
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# can never be later than now
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lastyear <- ifelse(lastyear > as.integer(format(Sys.Date(), "%Y")),
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NA,
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lastyear
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)
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# get authors without last year
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authors <- gsub("(.*)[0-9]{4}$", "\\1", authors2)
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# remove nonsense characters from names
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authors <- gsub("[^a-zA-Z,'& -]", "", authors)
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# remove trailing and leading spaces
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authors <- trimws(authors)
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# only keep first author and replace all others by 'et al'
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authors <- gsub("(,| and| et| &| ex| emend\\.?) .*", " et al.", authors)
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# et al. always with ending dot
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authors <- gsub(" et al\\.?", " et al.", authors)
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authors <- gsub(" ?,$", "", authors)
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# don't start with 'sensu' or 'ehrenb'
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authors <- gsub("^(sensu|Ehrenb.?) ", "", authors, ignore.case = TRUE)
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# no initials, only surname
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authors <- gsub("^([A-Z]+ )+", "", authors, ignore.case = FALSE)
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# combine author and year if year is available
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ref <- ifelse(!is.na(lastyear),
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paste0(authors, ", ", lastyear),
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authors
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)
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# fix beginning and ending
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ref <- gsub(", $", "", ref)
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ref <- gsub("^, ", "", ref)
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ref <- gsub("^(emend|et al.,?)", "", ref)
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ref <- trimws(ref)
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# a lot start with a lowercase character - fix that
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ref[!grepl("^d[A-Z]", ref)] <- gsub("^([a-z])", "\\U\\1", ref[!grepl("^d[A-Z]", ref)], perl = TRUE)
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# specific one for the French that are named dOrbigny
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ref[grepl("^d[A-Z]", ref)] <- gsub("^d", "d'", ref[grepl("^d[A-Z]", ref)])
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ref <- gsub(" +", " ", ref)
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ref
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}
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MOs <- MOs %>% mutate(ref = get_author_year(ref))
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# Remove non-ASCII characters (these are not allowed by CRAN)
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MOs <- MOs %>%
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lapply(iconv, from = "UTF-8", to = "ASCII//TRANSLIT") %>%
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as_tibble(stringsAsFactors = FALSE) %>%
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# remove invalid characters
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mutate_all(~ gsub("[\"'`]+", "", .))
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# set new fullnames
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MOs <- MOs %>%
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mutate(
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fullname = trimws(case_when(
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rank == "family" ~ family,
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rank == "order" ~ order,
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rank == "class" ~ class,
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rank == "phylum" ~ phylum,
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rank == "kingdom" ~ kingdom,
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TRUE ~ paste(genus, species, subspecies)
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)),
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fullname = gsub(" (var|f|subsp)[.]", "", fullname)
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) %>%
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# remove text if it contains 'Not assigned', etc.
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mutate_all(function(x) ifelse(x %like% "(not assigned|homonym|mistake)", NA, x)) %>%
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# clean taxonomy
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mutate(
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kingdom = ifelse(is.na(kingdom) | trimws(kingdom) == "", "(unknown kingdom)", trimws(kingdom)),
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phylum = ifelse(is.na(phylum) | trimws(phylum) == "", "(unknown phylum)", trimws(phylum)),
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class = ifelse(is.na(class) | trimws(class) == "", "(unknown class)", trimws(class)),
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order = ifelse(is.na(order) | trimws(order) == "", "(unknown order)", trimws(order)),
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family = ifelse(is.na(family) | trimws(family) == "", "(unknown family)", trimws(family))
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)
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# Split old taxonomic names
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MOs.old <- data_col_old %>%
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filter(!gsub(" (var|f|subsp)[.]", "", fullname_new) %in% data_dsmz_old$fullname) %>%
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bind_rows(data_dsmz_old) %>%
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mutate(
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fullname_new = gsub(" (var|f|subsp)[.]", "", fullname_new),
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fullname = gsub(" (var|f|subsp)[.]", "", fullname)
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) %>%
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# for cases like Chlamydia pneumoniae -> Chlamydophila pneumoniae -> Chlamydia pneumoniae:
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filter(!fullname %in% fullname_new &
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fullname_new %in% MOs$fullname &
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!is.na(fullname) &
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fullname != fullname_new) %>%
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distinct(fullname, .keep_all = TRUE) %>%
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arrange(fullname) %>%
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mutate(ref = get_author_year(ref))
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MOs <- MOs %>%
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# remove entries that are old and in MOs.old
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filter(!fullname %in% MOs.old$fullname) %>%
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# mark up
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transmute(fullname,
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kingdom,
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phylum,
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class,
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order,
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family,
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genus,
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species,
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subspecies,
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rank,
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ref,
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species_id = gsub("[^a-zA-Z0-9].*", "", species_id),
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source
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) %>%
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# prefer known taxonomy over unknown taxonomy, then DSMZ over CoL (= desc)
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arrange(desc(kingdom, genus, species, source)) %>%
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distinct(kingdom, fullname, .keep_all = TRUE)
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# remove all genera that have no species - they are irrelevant for microbiology and almost all from the kingdom of Animalia
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to_remove <- MOs %>%
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filter(!kingdom %in% c("Bacteria", "Protozoa")) %>%
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group_by(kingdom, genus) %>%
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count() %>%
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filter(n == 1) %>%
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ungroup() %>%
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mutate(kingdom_genus = paste(kingdom, genus)) %>%
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pull(kingdom_genus)
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MOs <- MOs %>% filter(!(paste(kingdom, genus) %in% to_remove))
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rm(to_remove)
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# add all mssing genera, families and orders
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MOs <- MOs %>%
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bind_rows(MOs %>%
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arrange(genus, species) %>%
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distinct(genus, .keep_all = TRUE) %>%
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filter(rank == "species") %>%
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mutate(
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fullname = genus,
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species = "",
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rank = "genus",
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species_id = "",
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ref = NA_character_
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)) %>%
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bind_rows(MOs %>%
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arrange(family, genus) %>%
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distinct(family, .keep_all = TRUE) %>%
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filter(rank == "genus") %>%
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mutate(
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fullname = family,
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genus = "",
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rank = "family",
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species_id = "",
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ref = NA_character_
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)) %>%
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bind_rows(MOs %>%
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arrange(order, family) %>%
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distinct(family, .keep_all = TRUE) %>%
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filter(rank == "family") %>%
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mutate(
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fullname = order,
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family = "",
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rank = "order",
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species_id = "",
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ref = NA_character_
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))
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# remove the empty ones
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MOs <- MOs %>%
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mutate(fullname = gsub(",.*", "", fullname)) %>%
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distinct(kingdom, fullname, .keep_all = TRUE) %>%
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filter(fullname != "")
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# what characters are in the fullnames?
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table(sort(unlist(strsplit(x = paste(MOs$fullname, collapse = ""), split = ""))))
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MOs %>%
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filter(fullname %unlike% "^[a-z ]+$") %>%
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arrange(fullname) %>%
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View()
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table(MOs$kingdom, MOs$rank)
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table(AMR::microorganisms$kingdom, AMR::microorganisms$rank)
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# set prevalence per species
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MOs <- MOs %>%
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mutate(prevalence = case_when(
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class == "Gammaproteobacteria" |
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genus %in% c("Enterococcus", "Staphylococcus", "Streptococcus")
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~ 1,
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kingdom %in% c("Archaea", "Bacteria", "Chromista", "Fungi") &
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(phylum %in% c(
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"Proteobacteria",
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"Firmicutes",
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"Actinobacteria",
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"Sarcomastigophora"
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) |
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genus %in% MO_PREVALENT_GENERA |
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rank %in% c("kingdom", "phylum", "class", "order", "family"))
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~ 2,
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TRUE ~ 3
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))
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# Add abbreviations so we can easily know which ones are which ones.
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# These will become valid and unique microbial IDs for the AMR package.
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MOs <- MOs %>%
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arrange(prevalence, genus, species, subspecies) %>%
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group_by(kingdom) %>%
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mutate(abbr_other = case_when(
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rank == "family" ~ paste0(
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"[FAM]_",
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abbreviate(family,
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minlength = 8,
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use.classes = TRUE,
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method = "both.sides",
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strict = FALSE
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)
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),
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rank == "order" ~ paste0(
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"[ORD]_",
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abbreviate(order,
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minlength = 8,
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use.classes = TRUE,
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method = "both.sides",
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strict = FALSE
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)
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),
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rank == "class" ~ paste0(
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"[CLS]_",
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abbreviate(class,
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minlength = 8,
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use.classes = TRUE,
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method = "both.sides",
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strict = FALSE
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)
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),
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rank == "phylum" ~ paste0(
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"[PHL]_",
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abbreviate(phylum,
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minlength = 8,
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use.classes = TRUE,
|
|
method = "both.sides",
|
|
strict = FALSE
|
|
)
|
|
),
|
|
rank == "kingdom" ~ paste0("[KNG]_", kingdom),
|
|
TRUE ~ NA_character_
|
|
)) %>%
|
|
# abbreviations may be same for genera between kingdoms,
|
|
# because each abbreviation starts with the the first character(s) of the kingdom
|
|
mutate(abbr_genus = abbreviate(gsub("^ae", "\u00E6\u00E6", genus, ignore.case = TRUE), # keep a starting Latin ae
|
|
minlength = 5,
|
|
use.classes = TRUE,
|
|
method = "both.sides"
|
|
)) %>%
|
|
ungroup() %>%
|
|
group_by(genus) %>%
|
|
# species abbreviations may be the same between genera
|
|
# because the genus abbreviation is part of the abbreviation
|
|
mutate(abbr_species = abbreviate(gsub("^ae", "\u00E6\u00E6", species),
|
|
minlength = 4,
|
|
use.classes = TRUE,
|
|
method = "both.sides"
|
|
)) %>%
|
|
ungroup() %>%
|
|
group_by(genus, species) %>%
|
|
mutate(abbr_subspecies = abbreviate(gsub("^ae", "\u00E6\u00E6", subspecies),
|
|
minlength = 4,
|
|
use.classes = TRUE,
|
|
method = "both.sides"
|
|
)) %>%
|
|
ungroup() %>%
|
|
# remove trailing underscores
|
|
mutate(
|
|
mo = gsub(
|
|
"_+$", "",
|
|
toupper(paste(ifelse(kingdom %in% c("Animalia", "Plantae"),
|
|
substr(kingdom, 1, 2),
|
|
substr(kingdom, 1, 1)
|
|
),
|
|
ifelse(is.na(abbr_other),
|
|
paste(abbr_genus,
|
|
abbr_species,
|
|
abbr_subspecies,
|
|
sep = "_"
|
|
),
|
|
abbr_other
|
|
),
|
|
sep = "_"
|
|
))
|
|
),
|
|
mo = gsub("(\u00C6|\u00E6)+", "AE", mo)
|
|
) %>%
|
|
mutate(
|
|
mo = ifelse(duplicated(.$mo),
|
|
# these one or two must be unique too
|
|
paste0(mo, "1"),
|
|
mo
|
|
),
|
|
fullname = ifelse(fullname == "",
|
|
trimws(paste(genus, species, subspecies)),
|
|
fullname
|
|
)
|
|
) %>%
|
|
# put `mo` in front, followed by the rest
|
|
select(mo, everything(), -abbr_other, -abbr_genus, -abbr_species, -abbr_subspecies)
|
|
|
|
# add non-taxonomic entries
|
|
MOs <- MOs %>%
|
|
bind_rows(
|
|
# Unknowns
|
|
data.frame(
|
|
mo = "UNKNOWN",
|
|
fullname = "(unknown name)",
|
|
kingdom = "(unknown kingdom)",
|
|
phylum = "(unknown phylum)",
|
|
class = "(unknown class)",
|
|
order = "(unknown order)",
|
|
family = "(unknown family)",
|
|
genus = "(unknown genus)",
|
|
species = "(unknown species)",
|
|
subspecies = "(unknown subspecies)",
|
|
rank = "(unknown rank)",
|
|
ref = NA_character_,
|
|
species_id = "",
|
|
source = "manually added",
|
|
prevalence = 1,
|
|
stringsAsFactors = FALSE
|
|
),
|
|
data.frame(
|
|
mo = "B_GRAMN",
|
|
fullname = "(unknown Gram-negatives)",
|
|
kingdom = "Bacteria",
|
|
phylum = "(unknown phylum)",
|
|
class = "(unknown class)",
|
|
order = "(unknown order)",
|
|
family = "(unknown family)",
|
|
genus = "(unknown Gram-negatives)",
|
|
species = "(unknown species)",
|
|
subspecies = "(unknown subspecies)",
|
|
rank = "species",
|
|
ref = NA_character_,
|
|
species_id = "",
|
|
source = "manually added",
|
|
prevalence = 1,
|
|
stringsAsFactors = FALSE
|
|
),
|
|
data.frame(
|
|
mo = "B_GRAMP",
|
|
fullname = "(unknown Gram-positives)",
|
|
kingdom = "Bacteria",
|
|
phylum = "(unknown phylum)",
|
|
class = "(unknown class)",
|
|
order = "(unknown order)",
|
|
family = "(unknown family)",
|
|
genus = "(unknown Gram-positives)",
|
|
species = "(unknown species)",
|
|
subspecies = "(unknown subspecies)",
|
|
rank = "species",
|
|
ref = NA_character_,
|
|
species_id = "",
|
|
source = "manually added",
|
|
prevalence = 1,
|
|
stringsAsFactors = FALSE
|
|
),
|
|
data.frame(
|
|
mo = "F_YEAST",
|
|
fullname = "(unknown yeast)",
|
|
kingdom = "Fungi",
|
|
phylum = "(unknown phylum)",
|
|
class = "(unknown class)",
|
|
order = "(unknown order)",
|
|
family = "(unknown family)",
|
|
genus = "(unknown genus)",
|
|
species = "(unknown species)",
|
|
subspecies = "(unknown subspecies)",
|
|
rank = "species",
|
|
ref = NA_character_,
|
|
species_id = "",
|
|
source = "manually added",
|
|
prevalence = 2,
|
|
stringsAsFactors = FALSE
|
|
),
|
|
data.frame(
|
|
mo = "F_FUNGUS",
|
|
fullname = "(unknown fungus)",
|
|
kingdom = "Fungi",
|
|
phylum = "(unknown phylum)",
|
|
class = "(unknown class)",
|
|
order = "(unknown order)",
|
|
family = "(unknown family)",
|
|
genus = "(unknown genus)",
|
|
species = "(unknown species)",
|
|
subspecies = "(unknown subspecies)",
|
|
rank = "species",
|
|
ref = NA_character_,
|
|
species_id = "",
|
|
source = "manually added",
|
|
prevalence = 2,
|
|
stringsAsFactors = FALSE
|
|
),
|
|
# CoNS
|
|
MOs %>%
|
|
filter(genus == "Staphylococcus", species == "epidermidis") %>%
|
|
.[1, ] %>%
|
|
mutate(
|
|
mo = gsub("(.*)_(.*)_.*", "\\1_\\2_CONS", mo),
|
|
species = "coagulase-negative",
|
|
fullname = "Coagulase-negative Staphylococcus (CoNS)",
|
|
ref = NA_character_,
|
|
species_id = "",
|
|
source = "manually added"
|
|
),
|
|
# CoPS
|
|
MOs %>%
|
|
filter(genus == "Staphylococcus", species == "epidermidis") %>%
|
|
.[1, ] %>%
|
|
mutate(
|
|
mo = gsub("(.*)_(.*)_.*", "\\1_\\2_COPS", mo),
|
|
species = "coagulase-positive",
|
|
fullname = "Coagulase-positive Staphylococcus (CoPS)",
|
|
ref = NA_character_,
|
|
species_id = "",
|
|
source = "manually added"
|
|
),
|
|
# Streptococci groups A, B, C, F, H, K
|
|
MOs %>%
|
|
filter(genus == "Streptococcus", species == "pyogenes") %>%
|
|
.[1, ] %>%
|
|
# we can keep all other details, since S. pyogenes is the only member of group A
|
|
mutate(
|
|
mo = gsub("(.*)_(.*)_.*", "\\1_\\2_GRPA", mo),
|
|
species = "group A",
|
|
fullname = "Streptococcus group A",
|
|
source = "manually added"
|
|
),
|
|
MOs %>%
|
|
filter(genus == "Streptococcus", species == "agalactiae") %>% .[1, ] %>%
|
|
# we can keep all other details, since S. agalactiae is the only member of group B
|
|
mutate(
|
|
mo = gsub("(.*)_(.*)_.*", "\\1_\\2_GRPB", mo),
|
|
species = "group B",
|
|
fullname = "Streptococcus group B",
|
|
source = "manually added"
|
|
),
|
|
MOs %>%
|
|
filter(genus == "Streptococcus", species == "dysgalactiae") %>% .[1, ] %>%
|
|
mutate(
|
|
mo = gsub("(.*)_(.*)_.*", "\\1_\\2_GRPC", mo),
|
|
species = "group C",
|
|
fullname = "Streptococcus group C",
|
|
ref = NA_character_,
|
|
species_id = "",
|
|
source = "manually added"
|
|
),
|
|
MOs %>%
|
|
filter(genus == "Streptococcus", species == "agalactiae") %>% .[1, ] %>%
|
|
mutate(
|
|
mo = gsub("(.*)_(.*)_.*", "\\1_\\2_GRPD", mo),
|
|
species = "group D",
|
|
fullname = "Streptococcus group D",
|
|
ref = NA_character_,
|
|
species_id = "",
|
|
source = "manually added"
|
|
),
|
|
MOs %>%
|
|
filter(genus == "Streptococcus", species == "agalactiae") %>% .[1, ] %>%
|
|
mutate(
|
|
mo = gsub("(.*)_(.*)_.*", "\\1_\\2_GRPF", mo),
|
|
species = "group F",
|
|
fullname = "Streptococcus group F",
|
|
ref = NA_character_,
|
|
species_id = "",
|
|
source = "manually added"
|
|
),
|
|
MOs %>%
|
|
filter(genus == "Streptococcus", species == "agalactiae") %>% .[1, ] %>%
|
|
mutate(
|
|
mo = gsub("(.*)_(.*)_.*", "\\1_\\2_GRPG", mo),
|
|
species = "group G",
|
|
fullname = "Streptococcus group G",
|
|
ref = NA_character_,
|
|
species_id = "",
|
|
source = "manually added"
|
|
),
|
|
MOs %>%
|
|
filter(genus == "Streptococcus", species == "agalactiae") %>% .[1, ] %>%
|
|
mutate(
|
|
mo = gsub("(.*)_(.*)_.*", "\\1_\\2_GRPH", mo),
|
|
species = "group H",
|
|
fullname = "Streptococcus group H",
|
|
ref = NA_character_,
|
|
species_id = "",
|
|
source = "manually added"
|
|
),
|
|
MOs %>%
|
|
filter(genus == "Streptococcus", species == "agalactiae") %>% .[1, ] %>%
|
|
mutate(
|
|
mo = gsub("(.*)_(.*)_.*", "\\1_\\2_GRPK", mo),
|
|
species = "group K",
|
|
fullname = "Streptococcus group K",
|
|
ref = NA_character_,
|
|
species_id = "",
|
|
source = "manually added"
|
|
),
|
|
# Beta haemolytic Streptococci
|
|
MOs %>%
|
|
filter(genus == "Streptococcus", species == "agalactiae") %>%
|
|
.[1, ] %>%
|
|
mutate(
|
|
mo = gsub("(.*)_(.*)_.*", "\\1_\\2_HAEM", mo),
|
|
species = "beta-haemolytic",
|
|
fullname = "Beta-haemolytic Streptococcus",
|
|
ref = NA_character_,
|
|
species_id = "",
|
|
source = "manually added"
|
|
),
|
|
# Viridans Streptococci
|
|
MOs %>%
|
|
filter(genus == "Streptococcus", species == "agalactiae") %>%
|
|
.[1, ] %>%
|
|
mutate(
|
|
mo = gsub("(.*)_(.*)_.*", "\\1_\\2_VIRI", mo),
|
|
species = "viridans",
|
|
fullname = "Viridans Group Streptococcus (VGS)",
|
|
ref = NA_character_,
|
|
species_id = "",
|
|
source = "manually added"
|
|
),
|
|
# Milleri Streptococci
|
|
MOs %>%
|
|
filter(genus == "Streptococcus", species == "agalactiae") %>%
|
|
.[1, ] %>%
|
|
mutate(
|
|
mo = gsub("(.*)_(.*)_.*", "\\1_\\2_MILL", mo),
|
|
species = "milleri",
|
|
fullname = "Milleri Group Streptococcus (MGS)",
|
|
ref = NA_character_,
|
|
species_id = "",
|
|
source = "manually added"
|
|
),
|
|
# Candida krusei
|
|
MOs %>%
|
|
filter(genus == "Candida", species == "glabrata") %>%
|
|
.[1, ] %>%
|
|
mutate(
|
|
mo = gsub("(.*)_(.*)_.*", "\\1_\\2_KRUS", mo),
|
|
species = "krusei",
|
|
fullname = "Candida krusei",
|
|
ref = NA_character_,
|
|
species_id = "",
|
|
source = "manually added"
|
|
),
|
|
# Blastocystis hominis does not exist (it means 'got a Blastocystis from humans', PMID 15634993)
|
|
# but let's be nice to the clinical people in microbiology
|
|
MOs %>%
|
|
filter(fullname == "Blastocystis") %>%
|
|
mutate(
|
|
mo = paste0(mo, "_HMNS"),
|
|
fullname = paste(fullname, "hominis"),
|
|
species = "hominis",
|
|
source = "manually added",
|
|
ref = NA_character_,
|
|
species_id = ""
|
|
),
|
|
# Trichomonas vaginalis is missing, same order as Dientamoeba
|
|
MOs %>%
|
|
filter(fullname == "Dientamoeba") %>%
|
|
mutate(
|
|
mo = gsub("(.*?)_.*", "\\1_THMNS", mo),
|
|
fullname = "Trichomonas",
|
|
family = "Trichomonadidae",
|
|
genus = "Trichomonas",
|
|
source = "manually added",
|
|
ref = "Donne, 1836",
|
|
species_id = ""
|
|
),
|
|
MOs %>%
|
|
filter(fullname == "Dientamoeba fragilis") %>%
|
|
mutate(
|
|
mo = gsub("(.*?)_.*", "\\1_THMNS_VAG", mo),
|
|
fullname = "Trichomonas vaginalis",
|
|
family = "Trichomonadidae",
|
|
genus = "Trichomonas",
|
|
species = "vaginalis",
|
|
source = "manually added",
|
|
ref = "Donne, 1836",
|
|
species_id = ""
|
|
),
|
|
MOs %>% # add family as such too
|
|
filter(fullname == "Monocercomonadidae") %>%
|
|
mutate(
|
|
mo = gsub("(.*)_(.*)_.*", "\\1_\\2_TRCHMNDD", mo),
|
|
fullname = "Trichomonadidae",
|
|
family = "Trichomonadidae",
|
|
rank = "family",
|
|
genus = "",
|
|
species = "",
|
|
source = "manually added",
|
|
ref = "",
|
|
species_id = ""
|
|
),
|
|
)
|
|
|
|
# Incorporate new microbial order for Gammaproteobacteria - Adeolu et al. (2016), PMID 27620848
|
|
MOs[which(MOs$family == "Enterobacteriaceae"), "family"] <- ""
|
|
MOs[which(MOs$genus %in% c(
|
|
"Escherichia",
|
|
"Atlantibacter",
|
|
"Biostraticola",
|
|
"Buttiauxella",
|
|
"Cedecea",
|
|
"Citrobacter",
|
|
"Cronobacter",
|
|
"Enterobacillus",
|
|
"Enterobacter",
|
|
"Franconibacter",
|
|
"Gibbsiella",
|
|
"Izhakiella",
|
|
"Klebsiella",
|
|
"Kluyvera",
|
|
"Kosakonia",
|
|
"Leclercia",
|
|
"Lelliottia",
|
|
"Mangrovibacter",
|
|
"Pluralibacter",
|
|
"Pseudocitrobacter",
|
|
"Raoultella",
|
|
"Rosenbergiella",
|
|
"Saccharobacter",
|
|
"Salmonella",
|
|
"Shigella",
|
|
"Shimwellia",
|
|
"Siccibacter",
|
|
"Trabulsiella",
|
|
"Yokenella"
|
|
)), "family"] <- "Enterobacteriaceae"
|
|
MOs[which(MOs$genus %in% c(
|
|
"Erwinia",
|
|
"Buchnera",
|
|
"Pantoea",
|
|
"Phaseolibacter",
|
|
"Tatumella",
|
|
"Wigglesworthia"
|
|
)), "family"] <- "Erwiniaceae"
|
|
MOs[which(MOs$genus %in% c(
|
|
"Pectobacterium",
|
|
"Brenneria",
|
|
"Dickeya",
|
|
"Lonsdalea",
|
|
"Sodalis"
|
|
)), "family"] <- "Pectobacteriaceae"
|
|
MOs[which(MOs$genus %in% c(
|
|
"Yersinia",
|
|
"Chania",
|
|
"Ewingella",
|
|
"Rahnella",
|
|
"Rouxiella",
|
|
"Samsonia",
|
|
"Serratia"
|
|
)), "family"] <- "Yersiniaceae"
|
|
MOs[which(MOs$genus %in% c(
|
|
"Hafnia",
|
|
"Edwardsiella",
|
|
"Obesumbacterium"
|
|
)), "family"] <- "Hafniaceae"
|
|
MOs[which(MOs$genus %in% c(
|
|
"Morganella",
|
|
"Arsenophonus",
|
|
"Cosenzaea",
|
|
"Moellerella",
|
|
"Photorhabdus",
|
|
"Proteus",
|
|
"Providencia",
|
|
"Xenorhabdus"
|
|
)), "family"] <- "Morganellaceae"
|
|
MOs[which(MOs$genus %in% c(
|
|
"Budvicia",
|
|
"Leminorella",
|
|
"Pragia"
|
|
)), "family"] <- "Budviciaceae"
|
|
MOs[which(MOs$family %in% c(
|
|
"Enterobacteriaceae",
|
|
"Erwiniaceae",
|
|
"Pectobacteriaceae",
|
|
"Yersiniaceae",
|
|
"Hafniaceae",
|
|
"Morganellaceae",
|
|
"Budviciaceae"
|
|
)), "order"] <- "Enterobacterales"
|
|
new_families <- MOs %>%
|
|
filter(order == "Enterobacterales") %>%
|
|
pull(family) %>%
|
|
unique()
|
|
|
|
MOs <- MOs %>%
|
|
filter(!(rank == "family" & fullname %in% new_families)) %>%
|
|
bind_rows(tibble(
|
|
mo = paste0(
|
|
"B_[FAM]_",
|
|
toupper(abbreviate(new_families,
|
|
minlength = 8,
|
|
use.classes = TRUE,
|
|
method = "both.sides",
|
|
strict = FALSE
|
|
))
|
|
),
|
|
fullname = new_families,
|
|
kingdom = "Bacteria",
|
|
phylum = "Proteobacteria",
|
|
class = "Gammaproteobacteria",
|
|
order = "Enterobacterales",
|
|
family = new_families,
|
|
genus = "",
|
|
species = "",
|
|
subspecies = "",
|
|
rank = "family",
|
|
ref = "Adeolu et al., 2016",
|
|
species_id = NA_character_,
|
|
source = "manually added",
|
|
prevalence = 1
|
|
))
|
|
|
|
MOs[which(MOs$order == "Enterobacteriales"), "order"] <- "Enterobacterales"
|
|
MOs[which(MOs$fullname == "Enterobacteriales"), "fullname"] <- "Enterobacterales"
|
|
|
|
# add prevalence to old taxonomic names
|
|
MOs.old <- MOs.old %>%
|
|
select(-prevalence) %>%
|
|
left_join(MOs %>% select(fullname, prevalence), by = c("fullname_new" = "fullname"))
|
|
|
|
# everything distinct?
|
|
sum(duplicated(MOs$mo))
|
|
sum(duplicated(MOs$fullname))
|
|
colnames(MOs)
|
|
|
|
# add the ones we would delete now, that have unexisting codes and names (also in the old names)
|
|
MOs <- MOs %>%
|
|
mutate(mo = as.character(mo)) %>%
|
|
bind_rows(
|
|
AMR::microorganisms %>%
|
|
mutate(mo = as.character(mo)) %>%
|
|
filter(genus %in% gen & !fullname %in% AMR::microorganisms$fullname &
|
|
!fullname %in% AMR::microorganisms.old$fullname &
|
|
!mo %in% microorganisms$mo) %>%
|
|
select(all_of(colnames(AMR::microorganisms)))
|
|
)
|
|
|
|
# here we welcome the new ones:
|
|
MOs %>%
|
|
arrange(fullname) %>%
|
|
filter(!fullname %in% AMR::microorganisms$fullname) %>%
|
|
View()
|
|
MOs.old %>%
|
|
arrange(fullname) %>%
|
|
filter(!fullname %in% AMR::microorganisms.old$fullname) %>%
|
|
View()
|
|
# and the ones we lost:
|
|
# AMR::microorganisms %>% filter(!fullname %in% MOs$fullname) %>% View() # based on fullname
|
|
AMR::microorganisms %>%
|
|
filter(!fullname %in% c(MOs$fullname, MOs.old$fullname)) %>%
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View() # excluding renamed ones
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# AMR::microorganisms %>% filter(!mo %in% MOs$mo) %>% View() # based on mo
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# AMR::microorganisms %>% filter(!mo %in% MOs$mo & !fullname %in% MOs$fullname) %>% View()
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# and these IDs have changed:
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old_new <- MOs %>%
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mutate(kingdom_fullname = paste(kingdom, fullname)) %>%
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filter(kingdom_fullname %in% (AMR::microorganisms %>%
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mutate(kingdom_fullname = paste(kingdom, fullname)) %>%
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pull(kingdom_fullname))) %>%
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left_join(AMR::microorganisms %>%
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mutate(kingdom_fullname = paste(kingdom, fullname)) %>%
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select(mo, kingdom_fullname), by = "kingdom_fullname", suffix = c("_new", "_old")) %>%
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filter(mo_new != mo_old) %>%
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select(mo_old, mo_new, everything())
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View(old_new)
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|
|
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# set new MO codes as names to existing data sets
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rsi_translation$mo <- mo_name(rsi_translation$mo, language = NULL)
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microorganisms.codes$mo <- mo_name(microorganisms.codes$mo, language = NULL)
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# microorganisms.translation <- AMR:::microorganisms.translation %>%
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# bind_rows(tibble(mo_old = AMR:::microorganisms.translation$mo_new, mo_new = mo_old)) %>%
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# filter(!mo_old %in% MOs$mo) %>%
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# mutate(mo_new = mo_name(mo_new, language = NULL)) %>%
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# bind_rows(old_new %>% select(mo_old, mo_new)) %>%
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# distinct(mo_old, .keep_all = TRUE)
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|
|
|
# arrange the data sets to save
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|
MOs <- MOs %>% arrange(fullname)
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|
MOs.old <- MOs.old %>% arrange(fullname)
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|
|
|
# transform
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|
MOs <- as.data.frame(MOs, stringsAsFactors = FALSE)
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|
MOs.old <- as.data.frame(MOs.old, stringsAsFactors = FALSE)
|
|
microorganisms.codes <- as.data.frame(microorganisms.codes, stringsAsFactors = FALSE)
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|
class(MOs$mo) <- c("mo", "character")
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|
|
|
# SAVE
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|
### for same server
|
|
microorganisms <- dataset_UTF8_to_ASCII(MOs)
|
|
microorganisms.old <- dataset_UTF8_to_ASCII(MOs.old)
|
|
### for other server
|
|
saveRDS(MOs, "microorganisms.rds")
|
|
saveRDS(MOs.old, "microorganisms.old.rds")
|
|
saveRDS(microorganisms.codes, "microorganisms.codes.rds")
|
|
|
|
# on the server, do:
|
|
usethis::use_data(microorganisms, overwrite = TRUE, version = 2)
|
|
usethis::use_data(microorganisms.old, overwrite = TRUE, version = 2)
|
|
rm(microorganisms)
|
|
rm(microorganisms.old)
|
|
|
|
# load new data sets
|
|
devtools::load_all(".")
|
|
|
|
# reset previously changed mo codes
|
|
rsi_translation$mo <- as.mo(rsi_translation$mo)
|
|
microorganisms.codes$mo <- as.mo(microorganisms.codes$mo)
|
|
class(microorganisms.codes$mo) <- c("mo", "character")
|
|
# microorganisms.translation <- microorganisms.translation %>%
|
|
# # (to do: add last package version to column pkg_version)
|
|
# left_join(microorganisms.old[, c("fullname", "fullname_new")], # microorganisms.old is now new and loaded
|
|
# by = c("mo_new" = "fullname")) %>%
|
|
# mutate(name = ifelse(!is.na(fullname_new), fullname_new, mo_new)) %>%
|
|
# left_join(microorganisms[, c("fullname", "mo")], # as is microorganisms
|
|
# by = c("name" = "fullname")) %>%
|
|
# select(mo_old, mo_new = mo) %>%
|
|
# filter(!is.na(mo_old), !is.na(mo_new))
|
|
# class(microorganisms.translation$mo_old) <- "character" # no class <mo> since those aren't valid MO codes
|
|
# class(microorganisms.translation$mo_new) <- c("mo", "character")
|
|
# save those to the package
|
|
usethis::use_data(rsi_translation, overwrite = TRUE, version = 2)
|
|
usethis::use_data(microorganisms.codes, overwrite = TRUE, version = 2)
|
|
# saveRDS(microorganisms.translation, file = "data-raw/microorganisms.translation.rds", version = 2)
|
|
# to save microorganisms.translation internally to the package
|
|
# source("data-raw/_pre_commit_hook.R")
|
|
|
|
# load new data sets again
|
|
devtools::load_all(".")
|
|
|
|
# and check: these codes should not be missing (will otherwise throw a unit test error):
|
|
AMR::microorganisms.codes %>% filter(!mo %in% MOs$mo)
|
|
AMR::rsi_translation %>% filter(!mo %in% MOs$mo)
|
|
# AMR:::microorganisms.translation %>% filter(!mo_new %in% MOs$mo)
|
|
|
|
# update the example_isolates data set
|
|
example_isolates$mo <- as.mo(example_isolates$mo)
|
|
usethis::use_data(example_isolates, overwrite = TRUE)
|
|
|
|
# Don't forget to add SNOMED codes! (data-raw/snomed.R)
|
|
|
|
# run the unit tests
|
|
testthat::test_file("tests/testthat/test-data.R")
|
|
testthat::test_file("tests/testthat/test-mo.R")
|
|
testthat::test_file("tests/testthat/test-mo_property.R")
|
|
|
|
# edit 2020-05-28
|
|
# Not sure why it now says M. tuberculosis was renamed to M. africanum (B_MYCBC_AFRC), but that's not true
|
|
microorganisms <- microorganisms %>%
|
|
bind_rows(microorganisms %>%
|
|
filter(mo == "B_MYCBC_AFRC") %>%
|
|
mutate(
|
|
mo = "B_MYCBC_TBRC", snomed = list(c("113861009", "113858008")),
|
|
ref = "Lehmann et al., 2018", species_id = "778540",
|
|
source = "DSMZ", species = "tuberculosis",
|
|
fullname = "Mycobacterium tuberculosis"
|
|
)) %>%
|
|
arrange(fullname)
|
|
class(microorganisms$mo) <- c("mo", "character")
|
|
microorganisms.old <- microorganisms.old %>% filter(fullname != "Mycobacterium tuberculosis")
|
|
|
|
usethis::use_data(microorganisms, overwrite = TRUE, version = 2, compress = "xz")
|
|
usethis::use_data(microorganisms.old, overwrite = TRUE, version = 2)
|
|
|
|
|
|
# OLD CODE ----------------------------------------------------------------
|
|
|
|
# to keep all the old IDs:
|
|
# MOs <- MOs %>% filter(!mo %in% old_new$mo_new) %>%
|
|
# rbind(microorganisms %>%
|
|
# filter(mo %in% old_new$mo_old) %>%
|
|
# select(mo, fullname) %>%
|
|
# left_join(MOs %>%
|
|
# select(-mo), by = "fullname"))
|
|
# this is how to fix it
|
|
# microorganisms.codes <- AMR::microorganisms.codes %>%
|
|
# left_join(MOs %>%
|
|
# mutate(kingdom_fullname = paste(kingdom, fullname)) %>%
|
|
# left_join(AMR::microorganisms %>%
|
|
# transmute(mo, kingdom_fullname = paste(kingdom, fullname)),
|
|
# by = "kingdom_fullname", suffix = c("_new", "_old")) %>%
|
|
# select(mo_old, mo_new),
|
|
# by = c("mo" = "mo_old")) %>%
|
|
# select(code, mo = mo_new) %>%
|
|
# filter(!is.na(mo))
|
|
# microorganisms.codes %>% filter(!mo %in% MOs$mo)
|
|
# # and for microorganisms.translation:
|
|
# microorganisms.translation <- AMR:::microorganisms.translation %>%
|
|
# select(mo = mo_new) %>%
|
|
# left_join(AMR::microorganisms %>%
|
|
# transmute(mo, kingdom_fullname = paste(kingdom, fullname)),
|
|
# by = "kingdom_fullname", suffix = c("_new", "_old")) %>%
|
|
# select(mo_old, mo_new)
|
|
# left_join(MOs %>%
|
|
# mutate(kingdom_fullname = paste(kingdom, fullname)) %>%
|
|
# left_join(AMR::microorganisms %>%
|
|
# transmute(mo, kingdom_fullname = paste(kingdom, fullname)),
|
|
# by = "kingdom_fullname", suffix = c("_new", "_old")) %>%
|
|
# select(mo_old, mo_new),
|
|
# by = c("mo" = "mo_old")) %>%
|
|
# select(code, mo = mo_new) %>%
|
|
# filter(!is.na(mo))
|
|
# microorganisms.codes %>% filter(!mo %in% MOs$mo)
|