mirror of https://github.com/msberends/AMR.git
502 lines
21 KiB
R
502 lines
21 KiB
R
# Reproduction of the `microorganisms` data set
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# Data retrieved from the Catalogue of Life (CoL) through the Encyclopaedia of Life:
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# https://opendata.eol.org/dataset/catalogue-of-life/
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# (download the resource file with a name like "Catalogue of Life yyyy-mm-dd")
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# and from the Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures
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# https://www.dsmz.de/support/bacterial-nomenclature-up-to-date-downloads.html
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# (download the latest "Complete List" as xlsx file)
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library(dplyr)
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library(AMR)
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# unzip and extract taxon.tab (around 1.5 GB) from the CoL archive, then:
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data_col <- data.table::fread("Downloads/taxon.tab")
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# read the xlsx file from DSMZ (only around 2.5 MB):
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data_dsmz <- readxl::read_xlsx("Downloads/DSMZ_bactnames.xlsx")
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# the CoL data is over 3.7M rows:
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data_col %>% freq(kingdom)
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# Item Count Percent Cum. Count Cum. Percent
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# --- ---------- ---------- -------- ----------- -------------
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# 1 Animalia 2,225,627 59.1% 2,225,627 59.1%
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# 2 Plantae 1,177,412 31.3% 3,403,039 90.4%
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# 3 Fungi 290,145 7.7% 3,693,184 98.1%
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# 4 Chromista 47,126 1.3% 3,740,310 99.3%
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# 5 Bacteria 14,478 0.4% 3,754,788 99.7%
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# 6 Protozoa 6,060 0.2% 3,760,848 99.9%
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# 7 Viruses 3,827 0.1% 3,764,675 100.0%
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# 8 Archaea 610 0.0% 3,765,285 100.0%
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# clean data_col
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data_col <- data_col %>%
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as_tibble() %>%
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select(col_id = taxonID,
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col_id_new = acceptedNameUsageID,
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fullname = scientificName,
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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 = furtherInformationURL)
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data_col$source <- "CoL"
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# clean data_dsmz
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data_dsmz <- data_dsmz %>%
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as_tibble() %>%
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transmute(col_id = NA_integer_,
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col_id_new = NA_integer_,
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fullname = "",
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# kingdom = "",
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# phylum = "",
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# class = "",
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# order = "",
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# family = "",
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genus = ifelse(is.na(GENUS), "", GENUS),
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species = ifelse(is.na(SPECIES), "", SPECIES),
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subspecies = ifelse(is.na(SUBSPECIES), "", SUBSPECIES),
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rank = ifelse(species == "", "genus", "species"),
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ref = AUTHORS,
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species_id = as.character(RECORD_NO),
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source = "DSMZ")
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# DSMZ only contains genus/(sub)species, try to find taxonomic properties based on genus and data_col
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ref_taxonomy <- data_col %>%
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filter(genus %in% data_dsmz$genus,
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family != "") %>%
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distinct(genus, .keep_all = TRUE) %>%
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select(kingdom, phylum, class, order, family, genus)
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data_dsmz <- data_dsmz %>%
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left_join(ref_taxonomy, by = "genus") %>%
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mutate(kingdom = "Bacteria",
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phylum = ifelse(is.na(phylum), "(unknown phylum)", phylum),
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class = ifelse(is.na(class), "(unknown class)", class),
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order = ifelse(is.na(order), "(unknown order)", order),
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family = ifelse(is.na(family), "(unknown family)", family),
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)
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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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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", "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% c("Absidia", "Acremonium", "Actinotignum", "Alternaria", "Anaerosalibacter", "Ancylostoma", "Anisakis", "Apophysomyces",
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"Arachnia", "Ascaris", "Aureobacterium", "Aureobasidium", "Balantidum", "Bilophilia", "Branhamella", "Brochontrix",
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"Brugia", "Calymmatobacterium", "Catabacter", "Cdc", "Chilomastix", "Chryseomonas", "Cladophialophora", "Cladosporium",
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"Clonorchis", "Cordylobia", "Curvularia", "Demodex", "Dermatobia", "Diphyllobothrium", "Dracunculus", "Echinococcus",
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"Enterobius", "Euascomycetes", "Exophiala", "Fasciola", "Fusarium", "Hendersonula", "Hymenolepis", "Kloeckera",
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"Koserella", "Larva", "Leishmania", "Lelliottia", "Loa", "Lumbricus", "Malassezia", "Metagonimus", "Molonomonas",
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"Mucor", "Nattrassia", "Necator", "Novospingobium", "Onchocerca", "Opistorchis", "Paragonimus", "Paramyxovirus",
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"Pediculus", "Phoma", "Phthirus", "Pityrosporum", "Pseudallescheria", "Pulex", "Rhizomucor", "Rhizopus", "Rhodotorula",
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"Salinococcus", "Sanguibacteroides", "Schistosoma", "Scopulariopsis", "Scytalidium", "Sporobolomyces", "Stomatococcus",
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"Strongyloides", "Syncephalastraceae", "Taenia", "Torulopsis", "Trichinella", "Trichobilharzia", "Trichomonas",
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"Trichosporon", "Trichuris", "Trypanosoma", "Wuchereria")
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# or the taxonomic entry is old - the species was renamed
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)
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# filter old taxonomic names so only the ones with an existing reference will be kept
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MOs <- MOs %>%
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filter(is.na(col_id_new) | (!is.na(col_id_new) & col_id_new %in% MOs$col_id))
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MOs <- MOs %>%
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# remove text if it contains 'Not assigned' like phylum in viruses
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mutate_all(~gsub("Not assigned", "", .))
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MOs <- MOs %>%
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# Only keep first author, e.g. transform 'Smith, Jones, 2011' to 'Smith et al., 2011':
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mutate(authors2 = iconv(ref, from = "UTF-8", to = "ASCII//TRANSLIT"),
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# remove leading and trailing brackets
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authors2 = gsub("^[(](.*)[)]$", "\\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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# get year from last 4 digits
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lastyear = as.integer(gsub(".*([0-9]{4})$", "\\1", authors2)),
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# can never be later than now
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lastyear = ifelse(lastyear > as.integer(format(Sys.Date(), "%Y")),
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NA,
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lastyear),
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# get authors without last year
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authors = gsub("(.*)[0-9]{4}$", "\\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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# fix beginning and ending
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ref = gsub(", $", "", ref),
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ref = gsub("^, ", "", ref)
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)
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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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# Split old taxonomic names - they refer in the original data to a new `taxonID` with `acceptedNameUsageID`
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MOs.old <- MOs %>%
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filter(!is.na(col_id_new),
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ref != "",
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source != "DSMZ") %>%
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transmute(col_id,
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col_id_new,
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fullname =
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trimws(
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gsub("(.*)[(].*", "\\1",
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stringr::str_replace(
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string = fullname,
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pattern = stringr::fixed(authors2),
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replacement = "")) %>%
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gsub(" (var|f|subsp)[.]", "", .)),
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ref) %>%
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filter(!is.na(fullname)) %>%
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distinct(fullname, .keep_all = TRUE) %>%
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arrange(col_id)
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MOs <- MOs %>%
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filter(is.na(col_id_new) | source == "DSMZ") %>%
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transmute(col_id,
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fullname = trimws(case_when(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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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 = gsub(":", "", 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-f0-9]+)", "\\1", species_id),
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source) %>%
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#distinct(fullname, .keep_all = TRUE) %>%
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filter(!grepl("unassigned", fullname, ignore.case = TRUE))
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# Filter out the DSMZ records that were renamed and are now in MOs.old
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MOs <- MOs %>%
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filter(!(source == "DSMZ" & fullname %in% MOs.old$fullname),
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!(source == "DSMZ" & fullname %in% (MOs %>% filter(source == "CoL") %>% pull(fullname)))) %>%
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distinct(fullname, .keep_all = TRUE)
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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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group_by(kingdom) %>%
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mutate(abbr_other = case_when(
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rank == "family" ~ paste0("[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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rank == "order" ~ paste0("[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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rank == "class" ~ paste0("[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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rank == "phylum" ~ paste0("[PHL]_",
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abbreviate(phylum,
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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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rank == "kingdom" ~ paste0("[KNG]_", kingdom),
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TRUE ~ NA_character_
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)) %>%
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# abbreviations may be same for genera between kingdoms,
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# because each abbreviation starts with the the first character(s) of the kingdom
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mutate(abbr_genus = abbreviate(genus,
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minlength = 5,
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use.classes = TRUE,
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method = "both.sides",
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strict = FALSE)) %>%
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ungroup() %>%
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group_by(genus) %>%
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# species abbreviations may be the same between genera
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# because the genus abbreviation is part of the abbreviation
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mutate(abbr_species = abbreviate(species,
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minlength = 3,
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use.classes = FALSE,
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method = "both.sides")) %>%
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ungroup() %>%
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group_by(genus, species) %>%
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mutate(abbr_subspecies = abbreviate(subspecies,
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minlength = 3,
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use.classes = FALSE,
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method = "both.sides")) %>%
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ungroup() %>%
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# remove trailing underscores
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mutate(mo = gsub("_+$", "",
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toupper(paste(ifelse(kingdom %in% c("Animalia", "Plantae"),
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substr(kingdom, 1, 2),
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substr(kingdom, 1, 1)),
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ifelse(is.na(abbr_other),
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paste(abbr_genus,
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abbr_species,
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abbr_subspecies,
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sep = "_"),
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abbr_other),
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sep = "_")))) %>%
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mutate(mo = ifelse(duplicated(.$mo),
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# these one or two must be unique too
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paste0(mo, "1"),
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mo),
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fullname = ifelse(fullname == "",
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trimws(paste(genus, species, subspecies)),
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fullname)) %>%
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# put `mo` in front, followed by the rest
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select(mo, everything(), -abbr_other, -abbr_genus, -abbr_species, -abbr_subspecies)
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# add non-taxonomic entries
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MOs <- MOs %>%
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bind_rows(
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# Unknowns
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data.frame(mo = "UNKNOWN",
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col_id = NA_integer_,
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fullname = "(unknown name)",
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kingdom = "(unknown kingdom)",
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phylum = "(unknown phylum)",
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class = "(unknown class)",
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order = "(unknown order)",
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family = "(unknown family)",
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genus = "(unknown genus)",
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species = "(unknown species)",
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subspecies = "(unknown subspecies)",
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rank = "(unknown rank)",
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ref = NA_character_,
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species_id = "",
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source = "manually added",
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stringsAsFactors = FALSE),
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data.frame(mo = "B_GRAMN",
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col_id = NA_integer_,
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fullname = "(unknown Gram negatives)",
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kingdom = "Bacteria",
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phylum = "(unknown phylum)",
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class = "(unknown class)",
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order = "(unknown order)",
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family = "(unknown family)",
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genus = "(unknown Gram negatives)",
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species = "(unknown species)",
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subspecies = "(unknown subspecies)",
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rank = "species",
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ref = NA_character_,
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species_id = "",
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source = "manually added",
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stringsAsFactors = FALSE),
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data.frame(mo = "B_GRAMP",
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col_id = NA_integer_,
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fullname = "(unknown Gram positives)",
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kingdom = "Bacteria",
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phylum = "(unknown phylum)",
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class = "(unknown class)",
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order = "(unknown order)",
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family = "(unknown family)",
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genus = "(unknown Gram positives)",
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species = "(unknown species)",
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subspecies = "(unknown subspecies)",
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rank = "species",
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ref = NA_character_,
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species_id = "",
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source = "manually added",
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stringsAsFactors = FALSE),
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# CoNS
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MOs %>%
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filter(genus == "Staphylococcus", species == "epidermidis") %>% .[1,] %>%
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mutate(mo = gsub("EPI", "CNS", mo),
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col_id = NA_integer_,
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species = "coagulase-negative",
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fullname = "Coagulase-negative Staphylococcus (CoNS)",
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ref = NA_character_,
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species_id = "",
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source = "manually added"),
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# CoPS
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MOs %>%
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filter(genus == "Staphylococcus", species == "epidermidis") %>% .[1,] %>%
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mutate(mo = gsub("EPI", "CPS", mo),
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col_id = NA_integer_,
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species = "coagulase-positive",
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fullname = "Coagulase-positive Staphylococcus (CoPS)",
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ref = NA_character_,
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species_id = "",
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source = "manually added"),
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# Streptococci groups A, B, C, F, H, K
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MOs %>%
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filter(genus == "Streptococcus", species == "pyogenes") %>% .[1,] %>%
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# we can keep all other details, since S. pyogenes is the only member of group A
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mutate(mo = gsub("PYO", "GRA", mo),
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species = "group A" ,
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fullname = "Streptococcus group A"),
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MOs %>%
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filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
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# we can keep all other details, since S. agalactiae is the only member of group B
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mutate(mo = gsub("AGA", "GRB", mo),
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species = "group B" ,
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fullname = "Streptococcus group B"),
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MOs %>%
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filter(genus == "Streptococcus", species == "dysgalactiae") %>% .[1,] %>%
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mutate(mo = gsub("DYS", "GRC", mo),
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col_id = NA_integer_,
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species = "group C" ,
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fullname = "Streptococcus group C",
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ref = NA_character_,
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species_id = "",
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source = "manually added"),
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MOs %>%
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filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
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mutate(mo = gsub("AGA", "GRD", mo),
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col_id = NA_integer_,
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species = "group D" ,
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fullname = "Streptococcus group D",
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ref = NA_character_,
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species_id = "",
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source = "manually added"),
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MOs %>%
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filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
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mutate(mo = gsub("AGA", "GRF", mo),
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col_id = NA_integer_,
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species = "group F" ,
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fullname = "Streptococcus group F",
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ref = NA_character_,
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species_id = "",
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source = "manually added"),
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MOs %>%
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filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
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mutate(mo = gsub("AGA", "GRG", mo),
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col_id = NA_integer_,
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species = "group G" ,
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fullname = "Streptococcus group G",
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ref = NA_character_,
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species_id = "",
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source = "manually added"),
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MOs %>%
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filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
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mutate(mo = gsub("AGA", "GRH", mo),
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col_id = NA_integer_,
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species = "group H" ,
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fullname = "Streptococcus group H",
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ref = NA_character_,
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species_id = "",
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source = "manually added"),
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MOs %>%
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filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
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mutate(mo = gsub("AGA", "GRK", mo),
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col_id = NA_integer_,
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species = "group K" ,
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fullname = "Streptococcus group K",
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ref = NA_character_,
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species_id = "",
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source = "manually added"),
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# Beta haemolytic Streptococci
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MOs %>%
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filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
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mutate(mo = gsub("AGA", "HAE", mo),
|
|
col_id = NA_integer_,
|
|
species = "beta-haemolytic" ,
|
|
fullname = "Beta-haemolytic Streptococcus",
|
|
ref = NA_character_,
|
|
species_id = "",
|
|
source = "manually added")
|
|
)
|
|
|
|
|
|
# everything distinct?
|
|
sum(duplicated(MOs$mo))
|
|
colnames(MOs)
|
|
|
|
# set prevalence per species
|
|
MOs <- MOs %>%
|
|
mutate(prevalence = case_when(
|
|
class == "Gammaproteobacteria"
|
|
| genus %in% c("Enterococcus", "Staphylococcus", "Streptococcus")
|
|
| mo == "UNKNOWN"
|
|
~ 1,
|
|
phylum %in% c("Proteobacteria",
|
|
"Firmicutes",
|
|
"Actinobacteria",
|
|
"Sarcomastigophora")
|
|
| genus %in% c("Aspergillus",
|
|
"Bacteroides",
|
|
"Candida",
|
|
"Capnocytophaga",
|
|
"Chryseobacterium",
|
|
"Cryptococcus",
|
|
"Elisabethkingia",
|
|
"Flavobacterium",
|
|
"Fusobacterium",
|
|
"Giardia",
|
|
"Leptotrichia",
|
|
"Mycoplasma",
|
|
"Prevotella",
|
|
"Rhodotorula",
|
|
"Treponema",
|
|
"Trichophyton",
|
|
"Ureaplasma")
|
|
| rank %in% c("kingdom", "phylum", "class", "order", "family")
|
|
~ 2,
|
|
TRUE ~ 3
|
|
))
|
|
|
|
# save it
|
|
MOs <- as.data.frame(MOs %>% arrange(fullname), stringsAsFactors = FALSE)
|
|
MOs.old <- as.data.frame(MOs.old, stringsAsFactors = FALSE)
|
|
class(MOs$mo) <- "mo"
|
|
|
|
saveRDS(MOs, "microorganisms.rds")
|
|
saveRDS(MOs.old, "microorganisms.old.rds")
|
|
|
|
# on the server:
|
|
usethis::use_data(microorganisms, overwrite = TRUE)
|
|
usethis::use_data(microorganisms.old, overwrite = TRUE)
|
|
rm(microorganisms)
|
|
rm(microorganisms.old)
|
|
# and update the year in R/data.R
|