freq() has moved to a new package, clean (CRAN link). Creating frequency tables is actually not the scope of this package (never was) and this function has matured a lot over the last two years. Therefore, a new package was created for data cleaning and checking and it perfectly fits the freq() function. The clean package is available on CRAN and will be installed automatically when updating the AMR package, that now imports it. In a later stage, the skewness() and kurtosis() functions will be moved to the clean package too.freq() has moved to a new package, clean (CRAN link). The freq() function still works, since it is re-exported from the clean package to this AMR package. Creating frequency tables is actually not the scope of this package (never was) and this function has matured a lot over the last two years. Therefore, a new package was created for data cleaning and checking and it perfectly fits the freq() function. The clean package is available on CRAN and will be installed automatically when updating the AMR package, that now imports it. In a later stage, the skewness() and kurtosis() functions will be moved to the clean package too.Determination of first isolates now excludes all ‘unknown’ microorganisms at default, i.e. microbial code "UNKNOWN". They can be included with the new parameter include_unknown:
Function bug_drug_combinations() to quickly get a data.frame with the antimicrobial resistance of any bug-drug combination in a data set:
x <- bug_drug_combinations(septic_patients)
+x
+#> ab mo S I R total
+#> 1 AMC B_ESCHR_COL 332 74 61 467
+#> 2 AMC B_KLBSL_PNE 49 3 6 58
+#> 3 AMC B_PROTS_MIR 28 7 1 36
+#> 4 AMC B_PSDMN_AER 0 0 30 30
+#> 5 AMC B_STPHY_AUR 234 0 1 235You can format this to a printable format, ready for reporting or exporting to e.g. Excel with the base R format() function:
Additional way to calculate co-resistance, i.e. when using multiple antibiotics as input for portion_* functions or count_* functions. This can be used to determine the empiric susceptibily of a combination therapy. A new parameter only_all_tested (which defaults to FALSE) replaces the old also_single_tested and can be used to select one of the two methods to count isolates and calculate portions. The difference can be seen in this example table (which is also on the portion and count help pages), where the %SI is being determined:
# -------------------------------------------------------------------------
-# only_all_tested = FALSE only_all_tested = TRUE
-# Antibiotic Antibiotic ----------------------- -----------------------
-# A B include as include as include as include as
-# numerator denominator numerator denominator
-# ---------- ---------- ---------- ----------- ---------- -----------
-# S S X X X X
-# I S X X X X
-# R S X X X X
-# not tested S X X - -
-# S I X X X X
-# I I X X X X
-# R I X X X X
-# not tested I X X - -
-# S R X X X X
-# I R X X X X
-# R R - X - X
-# not tested R - - - -
-# S not tested X X - -
-# I not tested X X - -
-# R not tested - - - -
-# not tested not tested - - - -
-# -------------------------------------------------------------------------# -------------------------------------------------------------------------
+# only_all_tested = FALSE only_all_tested = TRUE
+# Antibiotic Antibiotic ----------------------- -----------------------
+# A B include as include as include as include as
+# numerator denominator numerator denominator
+# ---------- ---------- ---------- ----------- ---------- -----------
+# S S X X X X
+# I S X X X X
+# R S X X X X
+# not tested S X X - -
+# S I X X X X
+# I I X X X X
+# R I X X X X
+# not tested I X X - -
+# S R X X X X
+# I R X X X X
+# R R - X - X
+# not tested R - - - -
+# S not tested X X - -
+# I not tested X X - -
+# R not tested - - - -
+# not tested not tested - - - -
+# -------------------------------------------------------------------------Since this is a major change, usage of the old also_single_tested will throw an informative error that it has been replaced by only_all_tested.
AMR:::get_column_abx())Added tibble printing support for classes rsi, mic, disk, ab mo. When using tibbles containing antibiotic columns, values S will print in green, values I will print in yellow and values R will print in red. Microbial IDs (class mo) will emphasise on the genus and species, not on the kingdom.
atc - using as.atc() is now deprecated in favour of ab_atc() and this will return a character, not the atc class anymoreabname(), ab_official(), atc_name(), atc_official(), atc_property(), atc_tradenames(), atc_trivial_nl()
@@ -318,7 +331,8 @@
antibiotics data set is now sorted by name and all cephalosporins now have their generation between bracketsguess_ab_col() which is now 30 times faster for antibiotic abbreviationsfilter_ab_class() to be more reliable and to support 5th generation cephalosporinsClasses ab and mo will now be preserved in any subsetting
ab and mo will now be preserved in any subsettingFunction availability() now uses portion_R() instead of portion_IR(), to comply with EUCAST insights
Function rsi_df() to transform a data.frame to a data set containing only the microbial interpretation (S, I, R), the antibiotic, the percentage of S/I/R and the number of available isolates. This is a convenient combination of the existing functions count_df() and portion_df() to immediately show resistance percentages and number of available isolates:
Support for all scientifically published pathotypes of E. coli to date (that we could find). Supported are:
@@ -364,12 +378,12 @@All these lead to the microbial ID of E. coli:
-as.mo("UPEC")
-# B_ESCHR_COL
-mo_name("UPEC")
-# "Escherichia coli"
-mo_gramstain("EHEC")
-# "Gram-negative"as.mo("UPEC")
+# B_ESCHR_COL
+mo_name("UPEC")
+# "Escherichia coli"
+mo_gramstain("EHEC")
+# "Gram-negative"mo_info() as an analogy to ab_info(). The mo_info() prints a list with the full taxonomy, authors, and the URL to the online database of a microorganismFunction mo_synonyms() to get all previously accepted taxonomic names of a microorganism
exact to determine ages with decimals
guess_mo(), guess_atc(), EUCAST_rules(), interpretive_reading(), rsi()
freq()):
+freq()):
support for boxplots:
- +freq() for when all values are NA
+freq() for when all values are NA
first_isolate() for when dates are missingguess_ab_col()
@@ -560,32 +574,32 @@ This data is updated annually - check the included version with the new function
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()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()New function 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:
-
+
New function availability() to check the number of available (non-empty) results in a data.frame
@@ -639,33 +653,33 @@ These functions use as.atc()
Now handles incorrect spelling, like i instead of y and f instead of ph:
-
+
Uncertainty of the algorithm is now divided into four levels, 0 to 3, where the default allow_uncertain = TRUE is equal to uncertainty level 2. Run ?as.mo for more info about these levels.
-# equal:
-as.mo(..., allow_uncertain = TRUE)
-as.mo(..., allow_uncertain = 2)
-
-# also equal:
-as.mo(..., allow_uncertain = FALSE)
-as.mo(..., allow_uncertain = 0)
+# equal:
+as.mo(..., allow_uncertain = TRUE)
+as.mo(..., allow_uncertain = 2)
+
+# also equal:
+as.mo(..., allow_uncertain = FALSE)
+as.mo(..., allow_uncertain = 0)
Using as.mo(..., allow_uncertain = 3) could lead to very unreliable results.
Implemented the latest publication of Becker et al. (2019), for categorising coagulase-negative Staphylococci
All microbial IDs that found are now saved to a local file ~/.Rhistory_mo. Use the new function clean_mo_history() to delete this file, which resets the algorithms.
Incoercible results will now be considered ‘unknown’, MO code UNKNOWN. On foreign systems, properties of these will be translated to all languages already previously supported: German, Dutch, French, Italian, Spanish and Portuguese:
-
+
Fix for vector containing only empty values
Finds better results when input is in other languages
@@ -707,23 +721,23 @@ Using as.mo(..., allow_uncertain = 3)
-Frequency tables (freq() function):
+ Frequency tables (freq() function):
-
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 info is now available as a list, with the
header function
- The parameter
header is now set to TRUE at default, even for markdown
@@ -798,10 +812,10 @@ Using as.mo(..., allow_uncertain = 3)Fewer than 3 characters as input for as.mo will return NA
Function as.mo (and all mo_* wrappers) now supports genus abbreviations with “species” attached
-
+
Added parameter 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)
Fix for portion_*(..., as_percent = TRUE) when minimal number of isolates would not be met
@@ -810,19 +824,19 @@ Using as.mo(..., allow_uncertain = 3)Using portion_* functions now throws a warning when total available isolate is below parameter minimum
Functions as.mo, as.rsi, as.mic, as.atc and freq will not set package name as attribute anymore
-Frequency tables - freq():
+ Frequency tables - freq():
-
Support for grouping variables, test with:
-
+
-
Support for (un)selecting columns:
-
+
- Check for
hms::is.hms
@@ -902,18 +916,18 @@ Using as.mo(..., allow_uncertain = 3)
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:
-
+
Functions count_R, count_IR, count_I, count_SI and count_S to selectively count resistant or susceptible isolates
@@ -924,18 +938,18 @@ Using as.mo(..., allow_uncertain = 3)
-
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 intelligent rules:
-as.mo("E. coli")
-# [1] B_ESCHR_COL
-as.mo("MRSA")
-# [1] B_STPHY_AUR
-as.mo("S group A")
-# [1] B_STRPTC_GRA
+as.mo("E. coli")
+# [1] B_ESCHR_COL
+as.mo("MRSA")
+# [1] B_STPHY_AUR
+as.mo("S group A")
+# [1] B_STRPTC_GRA
And 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:
-
+
- Added parameter
reference_df for as.mo, so users can supply their own microbial IDs, name or codes as a reference table
- Renamed all previous references to
bactid to mo, like:
@@ -963,12 +977,12 @@ Using as.mo(..., allow_uncertain = 3)Added three antimicrobial agents to the 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.:
-
+
- For
first_isolate, rows will be ignored when there’s no species available
- Function
ratio is now deprecated and will be removed in a future release, as it is not really the scope of this package
@@ -979,13 +993,13 @@ Using as.mo(..., allow_uncertain = 3)
-
Support for quasiquotation in the functions series count_* and portions_*, and n_rsi. This allows to check for more than 2 vectors or columns.
-
+
- Edited
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.
- Fix for
ggplot_rsi when the ggplot2 package was not loaded
@@ -999,12 +1013,12 @@ Using as.mo(..., allow_uncertain = 3)
-
Support for types (classes) list and matrix for freq
-
+
For lists, subsetting is possible:
-
+
as.mo(..., allow_uncertain = 3)
A vignette to explain its usage
Support for rsi (antimicrobial resistance) to use as input
-Support for table to use as input: freq(table(x, y))
+ Support for table to use as input: freq(table(x, y))
Support for existing functions hist and plot to use a frequency table as input: hist(freq(df$age))
Support for as.vector, as.data.frame, as_tibble and format
-Support for quasiquotation: freq(mydata, mycolumn) is the same as mydata %>% freq(mycolumn)
+ Support for quasiquotation: freq(mydata, mycolumn) is the same as mydata %>% freq(mycolumn)
Function top_freq function to return the top/below n items as vector
Header of frequency tables now also show Mean Absolute Deviaton (MAD) and Interquartile Range (IQR)
@@ -1238,7 +1252,7 @@ Using as.mo(..., allow_uncertain = 3)
Contents
Easy check for availability of columns in a data set. This makes it easy to get an idea of which antibiotic combination can be used for calculation with e.g. portion_IR.
Easy check for availability of columns in a data set. This makes it easy to get an idea of which antimicrobial combination can be used for calculation with e.g. portion_R.
data.frame with column names of tbl as row names
The function returns a data.frame with columns "resistant" and "visual_resistance". The values in that columns are calculated with portion_R.