mirror of https://github.com/msberends/AMR.git
257 lines
11 KiB
R
257 lines
11 KiB
R
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# Catalogue of Life
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# Data retrieved from Encyclopaedia of Life:
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# https://opendata.eol.org/dataset/catalogue-of-life/
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# unzip and extract taxon.tab, then:
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taxon <- data.table::fread("taxon.tab")
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# result is over 3.7M rows
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taxon %>% 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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MOs <- taxon %>%
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# tibble for future transformations
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as_tibble() %>%
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filter(
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# we only want all microorganisms and viruses
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!kingdom %in% c("Animalia", "Plantae"),
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# and no entries above genus - they all already have a taxonomic tree
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!taxonRank %in% c("kingdom", "phylum", "superfamily", "class", "order", "family"),
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# 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" & !order %in% c("Eurotiales", "Saccharomycetales", "Schizosaccharomycetales", "Onygenales", "Pneumocystales"))) %>%
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# remove text if it contains 'Not assigned' like phylum in viruses
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mutate_all(funs(gsub("Not assigned", "", .))) %>%
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# only latest ref, not original authors
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mutate(scientificNameAuthorship = trimws(gsub(".*[)] ", "", scientificNameAuthorship)),
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scientificNameAuthorship = ifelse(grepl(" emend[. ]", scientificNameAuthorship, ignore.case = TRUE),
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gsub("(.*)emend[. ]+(.*)", "\\2", scientificNameAuthorship, ignore.case = TRUE),
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scientificNameAuthorship),
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scientificNameAuthorship = gsub(".", "", scientificNameAuthorship, fixed = TRUE),
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scientificNameAuthorship = gsub(",? et al", " et al.", scientificNameAuthorship, fixed = FALSE, ignore.case = TRUE),
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scientificNameAuthorship = gsub("[()]", "", scientificNameAuthorship),
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# year always preceded by comma
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scientificNameAuthorship = gsub(" ([0-9]{4})$", ", \\1", scientificNameAuthorship),
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scientificNameAuthorship = gsub(",,", ",", scientificNameAuthorship, fixed = TRUE),
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# only first author with *et al.*
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scientificNameAuthorship = gsub(",.*,", " et al.,", scientificNameAuthorship),
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scientificNameAuthorship = gsub(" (and|&) .*,", " et al.,", scientificNameAuthorship),
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scientificNameAuthorship = gsub(", [^0-9]+", ", ", scientificNameAuthorship),
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scientificNameAuthorship = gsub(", $", "", scientificNameAuthorship)
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)
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# remove non-ASCII characters (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 to a new `taxonID` with `acceptedNameUsageID`
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MOs.old <- MOs %>%
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filter(!is.na(acceptedNameUsageID),
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scientificNameAuthorship != "") %>%
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transmute(col_id = taxonID,
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col_id_new = acceptedNameUsageID,
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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 = scientificName,
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pattern = stringr::fixed(scientificNameAuthorship),
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replacement = ""))),
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ref = scientificNameAuthorship) %>%
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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(acceptedNameUsageID)) %>%
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transmute(col_id = taxonID,
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fullname = trimws(ifelse(kingdom == "Viruses",
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paste(specificEpithet, infraspecificEpithet),
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paste(genus, specificEpithet, infraspecificEpithet))),
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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 = 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 = gsub(".*/([a-f0-9]+)", "\\1", furtherInformationURL)) %>%
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distinct(fullname, .keep_all = TRUE) %>%
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filter(!grepl("unassigned", fullname, ignore.case = TRUE))
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# only old names of species that are in MOs:
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MOs.old <- MOs.old %>% filter(col_id_new %in% MOs$col_id)
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MOs <- MOs %>%
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group_by(kingdom) %>%
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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 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("_+$", "",
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toupper(paste(substr(kingdom, 1, 1),
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abbr_genus,
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abbr_species,
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abbr_subspecies,
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sep = "_")))) %>%
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mutate(mo = ifelse(duplicated(.$mo), paste0(mo, "1"), mo)) %>%
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select(mo, everything(), -abbr_genus, -abbr_species, -abbr_subspecies)
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# everything distinct?
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sum(duplicated(MOs$mo))
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# add non-taxonomic entries
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MOs <- MOs %>%
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bind_rows(
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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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# 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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# Streptococci groups A, B, C, F, H, K
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MOs %>%
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filter(genus == "Streptococcus", species == "agalactiae") %>% .[1,] %>%
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mutate(mo = gsub("AGA", "GRA", mo),
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col_id = NA_integer_,
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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 == "dysgalactiae") %>% .[1,] %>%
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mutate(mo = gsub("DYS", "GRB", mo),
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col_id = NA_integer_,
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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 == "agalactiae") %>% .[1,] %>%
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mutate(mo = gsub("AGA", "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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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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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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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 F" ,
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fullname = "Streptococcus group G",
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ref = NA_character_),
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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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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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# 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),
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col_id = NA_integer_,
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species = "beta-haemolytic" ,
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fullname = "Beta-haemolytic Streptococcus",
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ref = NA_character_),
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# unknowns
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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 = NA_character_,
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class = NA_character_,
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order = NA_character_,
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family = NA_character_,
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genus = "(unknown Gram negatives)",
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species = NA_character_,
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subspecies = NA_character_,
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rank = "species",
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ref = NA_character_,
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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 = NA_character_,
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class = NA_character_,
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order = NA_character_,
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family = NA_character_,
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genus = "(unknown Gram positives)",
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species = NA_character_,
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subspecies = NA_character_,
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rank = "species",
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ref = NA_character_,
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stringsAsFactors = FALSE)
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)
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# save it
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MOs <- as.data.frame(MOs %>% arrange(mo), stringsAsFactors = FALSE)
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MOs.old <- as.data.frame(MOs.old, stringsAsFactors = FALSE)
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class(MOs$mo) <- "mo"
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saveRDS(MOs, "microorganisms.rds")
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saveRDS(MOs.old, "microorganisms.old.rds")
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# on the server:
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# usethis::use_data(microorganisms, overwrite = TRUE)
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# usethis::use_data(microorganisms.old, overwrite = TRUE)
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