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874 lines
39 KiB
R
874 lines
39 KiB
R
# ==================================================================== #
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# TITLE #
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# Antimicrobial Resistance (AMR) Analysis #
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# #
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# SOURCE #
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# https://gitlab.com/msberends/AMR #
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# #
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# LICENCE #
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# (c) 2018-2020 Berends MS, Luz CF et al. #
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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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# #
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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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# Visit our website for more info: https://msberends.gitlab.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) 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("data-raw/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("data-raw/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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kingdom %in% c("Bacteria", "Chromista", "Archaea", "Protozoa", "Fungi"),
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family != "") %>%
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mutate(kingdom = factor(kingdom,
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# in the left_join following, try Bacteria first, then Chromista, ...
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levels = c("Bacteria", "Chromista", "Archaea", "Protozoa", "Fungi"),
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ordered = TRUE)) %>%
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arrange(kingdom) %>%
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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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mo_found_in_NL <- c("Absidia", "Acremonium", "Actinotignum", "Aedes", "Alternaria", "Anaerosalibacter", "Ancylostoma",
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"Angiostrongylus", "Anisakis", "Anopheles", "Apophysomyces", "Arachnia", "Ascaris", "Aspergillus",
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"Aureobacterium", "Aureobasidium", "Bacteroides", "Balantidum", "Basidiobolus", "Beauveria",
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"Bilophilia", "Blastocystis", "Branhamella", "Brochontrix", "Brugia", "Calymmatobacterium", "Candida", "Capillaria",
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"Capnocytophaga", "Catabacter", "Cdc", "Chaetomium", "Chilomastix", "Chryseobacterium",
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"Chryseomonas", "Chrysonilia", "Cladophialophora", "Cladosporium", "Clonorchis", "Conidiobolus",
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"Contracaecum", "Cordylobia", "Cryptococcus", "Curvularia", "Demodex", "Dermatobia", "Dicrocoelium",
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"Dioctophyma", "Diphyllobothrium", "Dipylidium", "Dirofilaria", "Dracunculus", "Echinococcus",
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"Echinostoma", "Elisabethkingia", "Enterobius", "Enteromonas", "Euascomycetes", "Exophiala",
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"Exserohilum", "Fasciola", "Fasciolopsis", "Flavobacterium", "Fonsecaea", "Fusarium", "Fusobacterium",
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"Giardia", "Gnathostoma", "Hendersonula", "Heterophyes", "Hymenolepis", "Hypomyces",
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"Hysterothylacium", "Kloeckera", "Koserella", "Larva", "Lecythophora", "Leishmania", "Lelliottia",
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"Leptomyxida", "Leptosphaeria", "Leptotrichia", "Loa", "Lucilia", "Lumbricus", "Malassezia",
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"Malbranchea", "Mansonella", "Mesocestoides", "Metagonimus", "Metarrhizium", "Molonomonas",
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"Mortierella", "Mucor", "Multiceps", "Mycocentrospora", "Mycoplasma", "Nanophetus", "Nattrassia",
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"Necator", "Nectria", "Novospingobium", "Ochroconis", "Oesophagostomum", "Oidiodendron", "Onchocerca",
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"Opisthorchis", "Opistorchis", "Paragonimus", "Paramyxovirus", "Pediculus", "Phlebotomus",
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"Phocanema", "Phoma", "Phthirus", "Piedraia", "Pithomyces", "Pityrosporum", "Prevotella",
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"Pseudallescheria", "Pseudoterranova", "Pulex", "Retortamonas", "Rhizomucor", "Rhizopus",
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"Rhodotorula", "Salinococcus", "Sanguibacteroides", "Sarcophagidae", "Sarcoptes", "Schistosoma",
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"Scolecobasidium", "Scopulariopsis", "Scytalidium", "Spirometra", "Sporobolomyces", "Stachybotrys",
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"Stenotrophomononas", "Stomatococcus", "Strongyloides", "Syncephalastraceae", "Syngamus", "Taenia",
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"Ternidens", "Torulopsis", "Toxocara", "Toxoplasma", "Treponema", "Trichinella", "Trichobilharzia", "Trichoderma",
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"Trichomonas", "Trichophyton", "Trichosporon", "Trichostrongylus", "Trichuris", "Tritirachium",
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"Trombicula", "Trypanosoma", "Tunga", "Ureaplasma", "Wuchereria")
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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_found_in_NL
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# or the taxonomic entry is old - the species was renamed
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| !is.na(col_id_new)
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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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# 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$col_id))
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MOs <- MOs %>%
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# remove text if it contains 'Not assigned' like phylum in viruses
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mutate_all(~gsub("(Not assigned|\\[homonym\\]|\\[mistake\\])", "", ., ignore.case = TRUE))
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MOs <- MOs %>%
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# Only keep first author, e.g. transform 'Smith, Jones, 2011' to 'Smith et al., 2011':
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mutate(authors2 = iconv(ref, from = "UTF-8", to = "ASCII//TRANSLIT"),
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# remove leading and trailing brackets
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authors2 = gsub("^[(](.*)[)]$", "\\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(", $", "", ref),
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ref = gsub("^, ", "", ref),
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ref = gsub("^(emend|et al.,?)", "", ref),
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ref = trimws(ref)
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)
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# a lot start with a lowercase character - fix that
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MOs$ref[!grepl("^d[A-Z]", MOs$ref)] <- gsub("^([a-z])", "\\U\\1", MOs$ref[!grepl("^d[A-Z]", MOs$ref)], perl = TRUE)
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# specific one for the French that are named dOrbigny
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MOs$ref[grepl("^d[A-Z]", MOs$ref)] <- gsub("^d", "d'", MOs$ref[grepl("^d[A-Z]", MOs$ref)])
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MOs <- MOs %>% mutate(ref = gsub(" +", " ", 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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# 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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MO.bak <- MOs
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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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# prefer DSMZ over CoL, since that's more recent
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arrange(desc(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 CoL's col_id, source and ref from MOs.bak, for the cases where DSMZ took preference
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MOs <- MOs %>%
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mutate(kingdom_fullname = paste(kingdom, fullname)) %>%
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left_join(MO.bak %>%
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filter(is.na(col_id_new), !is.na(col_id)) %>%
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transmute(col_id, species_id, source, ref, kingdom_fullname = trimws(paste(kingdom, genus, species, subspecies))),
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by = "kingdom_fullname",
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suffix = c("_dsmz", "_col")) %>%
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mutate(col_id = col_id_col,
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species_id = ifelse(!is.na(species_id_col) & ref_col == ref_dsmz,
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gsub(".*/(.*)$", "\\1", species_id_col),
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species_id_dsmz),
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source = ifelse(!is.na(species_id_col) & ref_col == ref_dsmz,
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source_col,
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source_dsmz),
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ref = ifelse(!is.na(species_id_col) & ref_col == ref_dsmz,
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ref_col,
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ref_dsmz)) %>%
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select(-matches("(_col|_dsmz|kingdom_fullname)"))
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MOs.old <- MOs.old %>%
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# remove the ones that are in the MOs data set
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filter(col_id_new %in% MOs$col_id) %>%
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# and remove the ones that have the exact same fullname in the MOs data set, like Moraxella catarrhalis
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left_join(MOs, by = "fullname") %>%
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filter(col_id_new != col_id.y | is.na(col_id.y)) %>%
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select(col_id = col_id.x, col_id_new, fullname, ref = ref.x)
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# remove the records that are in MOs.old
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sum(MOs.old$fullname %in% MOs$fullname)
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MOs <- MOs %>% filter(!fullname %in% MOs.old$fullname)
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sum(MOs.old$fullname %in% MOs$fullname)
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# what characters are in the fullnames?
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table(sort(unlist(strsplit(x = paste(MOs$fullname, collapse = ""), split = ""))))
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MOs %>% filter(!fullname %like% "^[a-z ]+$") %>% 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("Proteobacteria",
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"Firmicutes",
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"Actinobacteria",
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"Sarcomastigophora")
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| genus %in% mo_found_in_NL
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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("[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(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",
|
|
col_id = NA_integer_,
|
|
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",
|
|
col_id = NA_integer_,
|
|
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",
|
|
col_id = NA_integer_,
|
|
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",
|
|
col_id = NA_integer_,
|
|
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",
|
|
col_id = NA_integer_,
|
|
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),
|
|
col_id = NA_integer_,
|
|
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),
|
|
col_id = NA_integer_,
|
|
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),
|
|
col_id = NA_integer_,
|
|
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),
|
|
col_id = NA_integer_,
|
|
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),
|
|
col_id = NA_integer_,
|
|
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),
|
|
col_id = NA_integer_,
|
|
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),
|
|
col_id = NA_integer_,
|
|
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),
|
|
col_id = NA_integer_,
|
|
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),
|
|
col_id = NA_integer_,
|
|
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),
|
|
col_id = NA_integer_,
|
|
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),
|
|
col_id = NA_integer_,
|
|
species = "milleri" ,
|
|
fullname = "Milleri Group Streptococcus (MGS)",
|
|
ref = NA_character_,
|
|
species_id = "",
|
|
source = "manually added"),
|
|
# Blastocystis hominis does not exist (it means 'got a Bastocystis 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",
|
|
col_id = NA,
|
|
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),
|
|
col_id = NA,
|
|
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),
|
|
col_id = NA,
|
|
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),
|
|
col_id = NA,
|
|
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$family %in% c("Enterobacteriaceae",
|
|
"Erwiniaceae",
|
|
"Pectobacteriaceae",
|
|
"Yersiniaceae",
|
|
"Hafniaceae",
|
|
"Morganellaceae",
|
|
"Budviciaceae")), "order"] <- "Enterobacterales"
|
|
new_families <- MOs %>%
|
|
filter(order == "Enterobacterales") %>%
|
|
pull(family) %>%
|
|
unique()
|
|
class(MOs$mo) <- "character"
|
|
MOs <- rbind(MOs %>% filter(!(rank == "family" & fullname %in% new_families)),
|
|
AMR::microorganisms %>%
|
|
filter(family == "Enterobacteriaceae" & rank == "family") %>%
|
|
rbind(., ., ., ., ., ., .) %>%
|
|
mutate(fullname = new_families,
|
|
source = "manually added",
|
|
ref = "Adeolu et al., 2016",
|
|
family = fullname, mo = paste0("B_[FAM]_",
|
|
toupper(abbreviate(new_families,
|
|
minlength = 8,
|
|
use.classes = TRUE,
|
|
method = "both.sides",
|
|
strict = FALSE)))))
|
|
MOs[which(MOs$order == "Enterobacteriales"), "order"] <- "Enterobacterales"
|
|
MOs[which(MOs$fullname == "Enterobacteriales"), "fullname"] <- "Enterobacterales"
|
|
|
|
MOs <- MOs %>%
|
|
group_by(kingdom) %>%
|
|
distinct(fullname, .keep_all = TRUE) %>%
|
|
ungroup() %>%
|
|
filter(fullname != "")
|
|
|
|
# add prevalence to old taxonomic names
|
|
MOs.old <- MOs.old %>%
|
|
left_join(MOs %>% select(col_id, prevalence), by = c("col_id_new" = "col_id"))
|
|
|
|
# everything distinct?
|
|
sum(duplicated(MOs$mo))
|
|
sum(duplicated(MOs$fullname))
|
|
colnames(MOs)
|
|
|
|
# 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$fullname) %>% View()
|
|
# and these IDs have changed:
|
|
old_new <- MOs %>%
|
|
mutate(kingdom_fullname = paste(kingdom, fullname)) %>%
|
|
filter(kingdom_fullname %in% (AMR::microorganisms %>% mutate(kingdom_fullname = paste(kingdom, fullname)) %>% pull(kingdom_fullname))) %>%
|
|
left_join(AMR::microorganisms %>% mutate(kingdom_fullname = paste(kingdom, fullname)) %>% select(mo, kingdom_fullname), by = "kingdom_fullname", suffix = c("_new", "_old")) %>%
|
|
filter(mo_new != mo_old) %>%
|
|
select(mo_old, mo_new, everything())
|
|
|
|
View(old_new)
|
|
# to keep all the old IDs:
|
|
# MOs <- MOs %>% filter(!mo %in% old_new$mo_new) %>%
|
|
# rbind(microorganisms %>%
|
|
# filter(mo %in% old_new$mo_old) %>%
|
|
# select(mo, fullname) %>%
|
|
# left_join(MOs %>%
|
|
# select(-mo), by = "fullname"))
|
|
|
|
# and these codes are now missing (which will throw a unit test error):
|
|
AMR::microorganisms.codes %>% filter(!mo %in% MOs$mo)
|
|
AMR::rsi_translation %>% filter(!mo %in% MOs$mo)
|
|
AMR::microorganisms.translation %>% filter(!mo_new %in% MOs$mo)
|
|
# this is how to fix it
|
|
microorganisms.codes <- AMR::microorganisms.codes %>%
|
|
left_join(MOs %>%
|
|
mutate(kingdom_fullname = paste(kingdom, fullname)) %>%
|
|
left_join(AMR::microorganisms %>%
|
|
mutate(kingdom_fullname = paste(kingdom, fullname)) %>%
|
|
select(mo, 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$mo)
|
|
|
|
# arrange
|
|
MOs <- MOs %>% arrange(fullname)
|
|
MOs.old <- MOs.old %>% arrange(fullname)
|
|
microorganisms.codes <- microorganisms.codes %>% arrange(code)
|
|
|
|
# transform
|
|
MOs <- as.data.frame(MOs, stringsAsFactors = FALSE)
|
|
MOs.old <- as.data.frame(MOs.old, stringsAsFactors = FALSE)
|
|
microorganisms.codes <- as.data.frame(microorganisms.codes, stringsAsFactors = FALSE)
|
|
class(MOs$mo) <- "mo"
|
|
class(microorganisms.codes$mo) <- "mo"
|
|
MOs$col_id <- as.integer(MOs$col_id)
|
|
MOs.old$col_id <- as.integer(MOs.old$col_id)
|
|
MOs.old$col_id_new <- as.integer(MOs.old$col_id_new)
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# SAVE
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### for other server
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saveRDS(MOs, "microorganisms.rds")
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|
saveRDS(MOs.old, "microorganisms.old.rds")
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|
saveRDS(microorganisms.codes, "microorganisms.codes.rds")
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|
### for same server
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|
microorganisms <- MOs
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|
microorganisms.old <- MOs.old
|
|
microorganisms.translation <- old_new %>% select(mo_old, mo_new)
|
|
class(microorganisms.translation$mo_old) <- "mo"
|
|
class(microorganisms.translation$mo_new) <- "mo"
|
|
|
|
# on the server, do:
|
|
usethis::use_data(microorganisms, overwrite = TRUE, version = 2)
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|
usethis::use_data(microorganisms.old, overwrite = TRUE, version = 2)
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|
usethis::use_data(microorganisms.codes, overwrite = TRUE, version = 2)
|
|
saveRDS(microorganisms.translation, file = "data-raw/microorganisms.translation.rds", version = 2) # this one will be covered in data-raw/internals.R
|
|
rm(microorganisms)
|
|
rm(microorganisms.old)
|
|
rm(microorganisms.codes)
|
|
rm(microorganisms.translation)
|
|
devtools::load_all(".")
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|
|
|
# TO DO AFTER THIS
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|
# * Update the year and dim()s in R/data.R
|
|
# * Rerun data-raw/reproduction_of_rsi_translation.R
|
|
# * Run unit tests
|