rsi <- random_rsi(10)
rsi
#> Class 'rsi'
-#> [1] I S I I S I R R S R
+#> [1] I S I S I R R S S I
mean_amr_distance(rsi)
-#> [1] -0.621059 -0.621059 -0.621059 -0.621059 -0.621059 -0.621059 1.449138
-#> [8] 1.449138 -0.621059 1.449138
+#> [1] -0.4743416 -0.4743416 -0.4743416 -0.4743416 -0.4743416 1.8973666
+#> [7] 1.8973666 -0.4743416 -0.4743416 -0.4743416
mic <- random_mic(10)
mic
#> Class 'mic'
-#> [1] 1 0.025 0.002 0.5 0.002 64 64 16 32 256
+#> [1] 0.5 0.125 0.005 64 2 0.5 0.002 1 >=256 16
mean_amr_distance(mic)
-#> [1] -0.07454929 -0.91041921 -1.48272867 -0.23161077 -1.48272867 0.86781961
-#> [7] 0.86781961 0.55369665 0.71075813 1.18194258
+#> [1] -0.13590568 -0.50369749 -1.35768361 1.15136563 0.23188612 -0.13590568
+#> [7] -1.60078077 0.04799022 1.51915743 0.78357383
# equal to the Z-score of their log2:
(log2(mic) - mean(log2(mic))) / sd(log2(mic))
-#> [1] -0.07454929 -0.91041921 -1.48272867 -0.23161077 -1.48272867 0.86781961
-#> [7] 0.86781961 0.55369665 0.71075813 1.18194258
+#> [1] -0.13590568 -0.50369749 -1.35768361 1.15136563 0.23188612 -0.13590568
+#> [7] -1.60078077 0.04799022 1.51915743 0.78357383
disk <- random_disk(10)
disk
#> Class 'disk'
-#> [1] 48 33 18 35 49 8 14 36 49 45
+#> [1] 19 35 29 49 16 45 40 46 43 44
mean_amr_distance(disk)
-#> [1] 0.94868330 -0.03271322 -1.01410973 0.09813965 1.01410973 -1.66837408
-#> [7] -1.27581547 0.16356609 1.01410973 0.75240400
+#> [1] -1.5151410 -0.1377401 -0.6542654 1.0674857 -1.7734036 0.7231355
+#> [7] 0.2926977 0.8092230 0.5509604 0.6370479
y <- data.frame(
id = LETTERS[1:10],
@@ -225,35 +225,35 @@
)
y
#> id amox cipr gent tobr
-#> 1 A I 19 8 0.5
-#> 2 B I 20 <=2 >=4
-#> 3 C I 29 <=2 >=4
-#> 4 D S 23 4 2
-#> 5 E S 29 4 >=4
-#> 6 F S 30 4 2
-#> 7 G S 19 16 2
-#> 8 H R 17 <=2 >=4
-#> 9 I R 29 16 0.5
-#> 10 J S 27 8 1
+#> 1 A I 22 1 1
+#> 2 B R 18 0.5 1
+#> 3 C S 29 4 4
+#> 4 D I 27 2 1
+#> 5 E I 18 8 1
+#> 6 F R 28 0.5 1
+#> 7 G I 29 2 >=8
+#> 8 H I 24 0.5 1
+#> 9 I S 30 2 4
+#> 10 J S 19 0.5 1
mean_amr_distance(y)
#> ℹ Calculating mean AMR distance based on columns "amox", "cipr", "gent" and
#> "tobr"
-#> [1] -0.61849512 -0.37440074 0.06535968 -0.22102136 0.28096952 0.12101452
-#> [7] 0.01474925 0.07193952 0.67866446 -0.01877971
+#> [1] -0.4635438 -0.2522842 0.6793050 -0.0301707 -0.1458327 0.2647728
+#> [7] 0.7200702 -0.5349771 0.5561661 -0.7935056
y$amr_distance <- mean_amr_distance(y, where(is.mic))
#> ℹ Calculating mean AMR distance based on columns "gent" and "tobr"
y[order(y$amr_distance), ]
#> id amox cipr gent tobr amr_distance
-#> 1 A I 19 8 0.5 -0.49165184
-#> 2 B I 20 <=2 >=4 -0.10118760
-#> 3 C I 29 <=2 >=4 -0.10118760
-#> 8 H R 17 <=2 >=4 -0.10118760
-#> 4 D S 23 4 2 -0.08760245
-#> 6 F S 30 4 2 -0.08760245
-#> 10 J S 27 8 1 -0.07401730
-#> 9 I R 29 16 0.5 -0.06043216
-#> 5 E S 29 4 >=4 0.33003208
-#> 7 G S 19 16 2 0.77483691
+#> 2 B R 18 0.5 1 -0.79141880
+#> 6 F R 28 0.5 1 -0.79141880
+#> 8 H I 24 0.5 1 -0.79141880
+#> 10 J S 19 0.5 1 -0.79141880
+#> 1 A I 22 1 1 -0.44172950
+#> 4 D I 27 2 1 -0.09204019
+#> 5 E I 18 8 1 0.60733841
+#> 9 I S 30 2 4 0.77039917
+#> 3 C S 29 4 4 1.12008847
+#> 7 G I 29 2 >=8 1.20161885
if (require("dplyr")) {
y %>%
@@ -265,17 +265,17 @@
}
#> ℹ Calculating mean AMR distance based on columns "amox", "cipr", "gent" and
#> "tobr"
-#> id amox cipr gent tobr amr_distance check_id_C
-#> 1 C I 29 <=2 >=4 0.06535968 0.000000000
-#> 2 H R 17 <=2 >=4 0.07193952 0.006579847
-#> 3 G S 19 16 2 0.01474925 0.050610425
-#> 4 F S 30 4 2 0.12101452 0.055654841
-#> 5 J S 27 8 1 -0.01877971 0.084139390
-#> 6 E S 29 4 >=4 0.28096952 0.215609840
-#> 7 D S 23 4 2 -0.22102136 0.286381034
-#> 8 B I 20 <=2 >=4 -0.37440074 0.439760411
-#> 9 I R 29 16 0.5 0.67866446 0.613304780
-#> 10 A I 19 8 0.5 -0.61849512 0.683854800
+#> id amox cipr gent tobr amr_distance check_id_C
+#> 1 C S 29 4 4 0.6793050 0.00000000
+#> 2 G I 29 2 >=8 0.7200702 0.04076519
+#> 3 I S 30 2 4 0.5561661 0.12313895
+#> 4 F R 28 0.5 1 0.2647728 0.41453227
+#> 5 D I 27 2 1 -0.0301707 0.70947573
+#> 6 E I 18 8 1 -0.1458327 0.82513769
+#> 7 B R 18 0.5 1 -0.2522842 0.93158924
+#> 8 A I 22 1 1 -0.4635438 1.14284886
+#> 9 H I 24 0.5 1 -0.5349771 1.21428212
+#> 10 J S 19 0.5 1 -0.7935056 1.47281060
if (require("dplyr")) {
# support for groups
example_isolates %>%
diff --git a/reference/microorganisms.codes.html b/reference/microorganisms.codes.html
index a380f709..7485ddee 100644
--- a/reference/microorganisms.codes.html
+++ b/reference/microorganisms.codes.html
@@ -10,7 +10,7 @@
AMR (for R)
- 1.8.2.9090
+ 1.8.2.9091