The responsible author(s) and year of scientific publication
This data is updated annually - check the included version with the new functioncatalogue_of_life_version().
mo codes changed (e.g. Streptococcus changed from B_STRPTC to B_STRPT). A translation table is used internally to support older microorganism IDs, so users will not notice this difference.mo_rank() for the taxonomic rank (genus, species, infraspecies, etc.)mo_url() to get the direct URL of a species from the Catalogue of Lifemo_rank() for the taxonomic rank (genus, species, infraspecies, etc.)mo_url() to get the URL to the Catalogue of Lifefirst_isolate() and eucast_rules(), all parameters will be filled in automatically.New filters for antimicrobial classes. Use these functions to filter isolates on results in one of more antibiotics from a specific class:
+filter_aminoglycosides()
+filter_carbapenems()
+filter_cephalosporins()
+filter_1st_cephalosporins()
+filter_2nd_cephalosporins()
+filter_3rd_cephalosporins()
+filter_4th_cephalosporins()
+filter_fluoroquinolones()
+filter_glycopeptides()
+filter_macrolides()
+filter_tetracyclines()The antibiotics data set will be searched, after which the input data will be checked for column names with a value in any abbreviations, codes or official names found in the antibiotics data set. For example:
All ab_* functions are deprecated and replaced by atc_* functions:
ab_property -> atc_property()
-ab_name -> atc_name()
-ab_official -> atc_official()
-ab_trivial_nl -> atc_trivial_nl()
-ab_certe -> atc_certe()
-ab_umcg -> atc_umcg()
-ab_tradenames -> atc_tradenames()ab_property -> atc_property()
+ab_name -> atc_name()
+ab_official -> atc_official()
+ab_trivial_nl -> atc_trivial_nl()
+ab_certe -> atc_certe()
+ab_umcg -> atc_umcg()
+ab_tradenames -> atc_tradenames()as.atc() internally. The old atc_property has been renamed atc_online_property(). This is done for two reasons: firstly, not all ATC codes are of antibiotics (ab) but can also be of antivirals or antifungals. Secondly, the input must have class atc or must be coerable to this class. Properties of these classes should start with the same class name, analogous to as.mo() and e.g. mo_genus.set_mo_source() and get_mo_source() to use your own predefined MO codes as input for as.mo() and consequently all mo_* functionsdplyr version 0.8.0as.atc()
age_groups() to split ages into custom or predefined groups (like children or elderly). This allows for easier demographic antimicrobial resistance analysis per age group.New function ggplot_rsi_predict() as well as the base R plot() function can now be used for resistance prediction calculated with resistance_predict():
Functions filter_first_isolate() and filter_first_weighted_isolate() to shorten and fasten filtering on data sets with antimicrobial results, e.g.:
is equal to:
- +availability() to check the number of available (non-empty) results in a data.frame
as.atc()
UNKNOWN. Properties of these will be translated on foreign systems in all language already previously supported: German, Dutch, French, Italian, Spanish and Portuguese:mo_genus("qwerty", language = "es")
-# Warning:
-# one unique value (^= 100.0%) could not be coerced and is considered 'unknown': "qwerty". Use mo_failures() to review it.
-#> [1] "(género desconocido)"mo_genus("qwerty", language = "es")
+# Warning:
+# one unique value (^= 100.0%) could not be coerced and is considered 'unknown': "qwerty". Use mo_failures() to review it.
+#> [1] "(género desconocido)"as.atc()
Support for tidyverse quasiquotation! Now you can create frequency tables of function outcomes:
-# Determine genus of microorganisms (mo) in `septic_patients` data set:
-# OLD WAY
-septic_patients %>%
- mutate(genus = mo_genus(mo)) %>%
- freq(genus)
-# NEW WAY
-septic_patients %>%
- freq(mo_genus(mo))
-
-# Even supports grouping variables:
-septic_patients %>%
- group_by(gender) %>%
- freq(mo_genus(mo))# Determine genus of microorganisms (mo) in `septic_patients` data set:
+# OLD WAY
+septic_patients %>%
+ mutate(genus = mo_genus(mo)) %>%
+ freq(genus)
+# NEW WAY
+septic_patients %>%
+ freq(mo_genus(mo))
+
+# Even supports grouping variables:
+septic_patients %>%
+ group_by(gender) %>%
+ freq(mo_genus(mo))header functionheader is now set to TRUE at default, even for markdownas.atc()
as.mo will return NAFunction as.mo (and all mo_* wrappers) now supports genus abbreviations with “species” attached
combine_IR (TRUE/FALSE) to functions portion_df and count_df, to indicate that all values of I and R must be merged into one, so the output only consists of S vs. IR (susceptible vs. non-susceptible)portion_*(..., as_percent = TRUE) when minimal number of isolates would not be metas.atc()
Support for grouping variables, test with:
- +Support for (un)selecting columns:
- +hms::is.hms
as.atc()
They also come with support for German, Dutch, French, Italian, Spanish and Portuguese:
-mo_gramstain("E. coli")
-# [1] "Gram negative"
-mo_gramstain("E. coli", language = "de") # German
-# [1] "Gramnegativ"
-mo_gramstain("E. coli", language = "es") # Spanish
-# [1] "Gram negativo"
-mo_fullname("S. group A", language = "pt") # Portuguese
-# [1] "Streptococcus grupo A"mo_gramstain("E. coli")
+# [1] "Gram negative"
+mo_gramstain("E. coli", language = "de") # German
+# [1] "Gramnegativ"
+mo_gramstain("E. coli", language = "es") # Spanish
+# [1] "Gram negativo"
+mo_fullname("S. group A", language = "pt") # Portuguese
+# [1] "Streptococcus grupo A"Furthermore, former taxonomic names will give a note about the current taxonomic name:
-mo_gramstain("Esc blattae")
-# Note: 'Escherichia blattae' (Burgess et al., 1973) was renamed 'Shimwellia blattae' (Priest and Barker, 2010)
-# [1] "Gram negative"mo_gramstain("Esc blattae")
+# Note: 'Escherichia blattae' (Burgess et al., 1973) was renamed 'Shimwellia blattae' (Priest and Barker, 2010)
+# [1] "Gram negative"count_R, count_IR, count_I, count_SI and count_S to selectively count resistant or susceptible isolates
as.atc()
Functions as.mo and is.mo as replacements for as.bactid and is.bactid (since the microoganisms data set not only contains bacteria). These last two functions are deprecated and will be removed in a future release. The as.mo function determines microbial IDs using Artificial Intelligence (AI):
as.mo("E. coli")
-# [1] B_ESCHR_COL
-as.mo("MRSA")
-# [1] B_STPHY_AUR
-as.mo("S group A")
-# [1] B_STRPTC_GRAas.mo("E. coli")
+# [1] B_ESCHR_COL
+as.mo("MRSA")
+# [1] B_STPHY_AUR
+as.mo("S group A")
+# [1] B_STRPTC_GRAAnd with great speed too - on a quite regular Linux server from 2007 it takes us less than 0.02 seconds to transform 25,000 items:
- +reference_df for as.mo, so users can supply their own microbial IDs, name or codes as a reference tablebactid to mo, like:
@@ -632,12 +651,12 @@ These functions use as.atc()
antibiotics data set: Terbinafine (D01BA02), Rifaximin (A07AA11) and Isoconazole (D01AC05)Added 163 trade names to the antibiotics data set, it now contains 298 different trade names in total, e.g.:
first_isolate, rows will be ignored when there’s no species availableratio is now deprecated and will be removed in a future release, as it is not really the scope of this packageas.atc()
Support for quasiquotation in the functions series count_* and portions_*, and n_rsi. This allows to check for more than 2 vectors or columns.
ggplot_rsi and geom_rsi so they can cope with count_df. The new fun parameter has value portion_df at default, but can be set to count_df.ggplot_rsi when the ggplot2 package was not loadedas.atc()
Support for types (classes) list and matrix for freq
For lists, subsetting is possible:
- +The antibioticsab_class in the columns atc_group1 and atc_group2 (case-insensitive). Next, tbl will be checked for column names with a value in any abbreviations, codes or official names found in the antibiotics data set.
The antibiotics data set will be searched for ab_class in the columns atc_group1 and atc_group2 (case-insensitive). Next, tbl will be checked for column names with a value in any abbreviations, codes or official names found in the antibiotics data set.