Use these selection helpers inside any function that allows Tidyverse selection helpers, like dplyr::select()
or tidyr::pivot_longer()
. They help to select the columns of antibiotics that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations.
ab_class(ab_class) aminoglycosides() carbapenems() cephalosporins() cephalosporins_1st() cephalosporins_2nd() cephalosporins_3rd() cephalosporins_4th() cephalosporins_5th() fluoroquinolones() glycopeptides() macrolides() penicillins() tetracyclines()
ab_class | an antimicrobial class, like |
---|
All columns will be searched for known antibiotic names, abbreviations, brand names and codes (ATC, EARS-Net, WHO, etc.) in the antibiotics data set. This means that a selector like e.g. aminoglycosides()
will pick up column names like 'gen', 'genta', 'J01GB03', 'tobra', 'Tobracin', etc.
N.B. These functions only work if the tidyselect
package is installed, that comes with the dplyr
package. An error will be thrown if the tidyselect
package is not installed, or if the functions are used outside a function that allows Tidyverse selections like select()
or pivot_longer()
.
All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this AMR
package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find all download links on our website, which is automatically updated with every code change.
On our website https://msberends.github.io/AMR/ you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions and an example analysis using WHONET data. As we would like to better understand the backgrounds and needs of our users, please participate in our survey!
filter_ab_class()
for the filter()
equivalent.
if (require("dplyr")) { # this will select columns 'IPM' (imipenem) and 'MEM' (meropenem): example_isolates %>% select(carbapenems()) # this will select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB': example_isolates %>% select(mo, aminoglycosides()) # this will select columns 'mo' and all antimycobacterial drugs ('RIF'): example_isolates %>% select(mo, ab_class("mycobact")) # get bug/drug combinations for only macrolides in Gram-positives: example_isolates %>% filter(is_gram_positive()) %>% select(mo, macrolides()) %>% bug_drug_combinations() %>% format() data.frame(some_column = "some_value", J01CA01 = "S") %>% # ATC code of ampicillin select(penicillins()) # only the 'J01CA01' column will be selected }