rsi <- random_rsi(10)
rsi
#> Class 'rsi'
-#> [1] I R I I S I S I I I
+#> [1] S S R I I R R R I S
mean_amr_distance(rsi)
-#> [1] -0.3162278 2.8460499 -0.3162278 -0.3162278 -0.3162278 -0.3162278
-#> [7] -0.3162278 -0.3162278 -0.3162278 -0.3162278
+#> [1] -0.7745967 -0.7745967 1.1618950 -0.7745967 -0.7745967 1.1618950
+#> [7] 1.1618950 1.1618950 -0.7745967 -0.7745967
mic <- random_mic(10)
mic
#> Class 'mic'
-#> [1] 256 <=0.001 0.005 0.5 0.25 4 32 128 64
-#> [10] 256
+#> [1] 32 0.001 >=64 0.01 0.001 2 0.002 0.005 0.002 0.125
mean_amr_distance(mic)
-#> [1] 0.99293867 -1.76809231 -1.41125204 -0.39020601 -0.54388875 0.07084222
-#> [7] 0.53189044 0.83925593 0.68557318 0.99293867
+#> [1] 1.5006685 -0.9103327 1.6617694 -0.3751671 -0.9103327 0.8562649
+#> [7] -0.7492318 -0.5362680 -0.7492318 0.2118614
# equal to the Z-score of their log2:
(log2(mic) - mean(log2(mic))) / sd(log2(mic))
-#> [1] 0.99293867 -1.76809231 -1.41125204 -0.39020601 -0.54388875 0.07084222
-#> [7] 0.53189044 0.83925593 0.68557318 0.99293867
+#> [1] 1.5006685 -0.9103327 1.6617694 -0.3751671 -0.9103327 0.8562649
+#> [7] -0.7492318 -0.5362680 -0.7492318 0.2118614
disk <- random_disk(10)
disk
#> Class 'disk'
-#> [1] 19 33 22 41 43 10 7 15 48 7
+#> [1] 50 50 42 10 25 25 24 41 14 46
mean_amr_distance(disk)
-#> [1] -0.3527042 0.5450884 -0.1603201 1.0581127 1.1863688 -0.9298566
-#> [7] -1.1222407 -0.6092164 1.5070090 -1.1222407
+#> [1] 1.1634023 1.1634023 0.6254128 -1.5265452 -0.5178149 -0.5178149
+#> [7] -0.5850636 0.5581641 -1.2575504 0.8944075
y <- data.frame(
id = LETTERS[1:10],
@@ -225,36 +224,36 @@
tobr = random_mic(10, ab = "tobr", mo = "Escherichia coli")
)
y
-#> id amox cipr gent tobr
-#> 1 A S 24 8 1
-#> 2 B S 29 2 <=0.25
-#> 3 C R 21 16 >=4
-#> 4 D R 28 8 0.5
-#> 5 E I 24 4 0.5
-#> 6 F R 27 16 2
-#> 7 G S 18 8 0.5
-#> 8 H R 30 8 2
-#> 9 I R 18 <=0.5 <=0.25
-#> 10 J S 21 <=0.5 <=0.25
+#> id amox cipr gent tobr
+#> 1 A I 28 1 <=1
+#> 2 B S 18 2 8
+#> 3 C S 26 >=8 8
+#> 4 D R 28 >=8 8
+#> 5 E I 31 2 8
+#> 6 F R 23 1 8
+#> 7 G R 23 4 8
+#> 8 H I 31 4 <=1
+#> 9 I I 18 >=8 4
+#> 10 J I 17 2 2
mean_amr_distance(y)
#> ℹ Calculating mean AMR distance based on columns "amox", "cipr", "gent" and
#> "tobr"
-#> [1] -0.0285555 -0.3644751 0.7598507 0.4975482 -0.3378487 0.9246795
-#> [7] -0.5421272 0.9593579 -0.7818441 -1.0865856
+#> [1] -0.7306638 -0.4034429 0.3974553 1.0087361 0.2058131 0.1354498
+#> [7] 0.5614212 -0.1640949 -0.1717694 -0.8389046
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
-#> 9 I R 18 <=0.5 <=0.25 -1.35962934
-#> 10 J S 21 <=0.5 <=0.25 -1.35962934
-#> 2 B S 29 2 <=0.25 -0.81994226
-#> 5 E I 24 4 0.5 -0.20135581
-#> 4 D R 28 8 0.5 0.06848772
-#> 7 G S 18 8 0.5 0.06848772
-#> 1 A S 24 8 1 0.41723064
-#> 8 H R 30 8 2 0.76597356
-#> 6 F R 27 16 2 1.03581709
-#> 3 C R 21 16 >=4 1.38456001
+#> id amox cipr gent tobr amr_distance
+#> 1 A I 28 1 <=1 -1.49760542
+#> 10 J I 17 2 2 -0.68303823
+#> 8 H I 31 4 <=1 -0.64566267
+#> 6 F R 23 1 8 -0.33181796
+#> 2 B S 18 2 8 0.09415341
+#> 5 E I 31 2 8 0.09415341
+#> 7 G R 23 4 8 0.52012479
+#> 9 I I 18 >=8 4 0.55750034
+#> 3 C S 26 >=8 8 0.94609616
+#> 4 D R 28 >=8 8 0.94609616
if (require("dplyr")) {
y %>%
@@ -266,17 +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 R 21 16 >=4 0.7598507 0.0000000
-#> 2 F R 27 16 2 0.9246795 0.1648288
-#> 3 H R 30 8 2 0.9593579 0.1995072
-#> 4 D R 28 8 0.5 0.4975482 0.2623025
-#> 5 A S 24 8 1 -0.0285555 0.7884062
-#> 6 E I 24 4 0.5 -0.3378487 1.0976994
-#> 7 B S 29 2 <=0.25 -0.3644751 1.1243258
-#> 8 G S 18 8 0.5 -0.5421272 1.3019779
-#> 9 I R 18 <=0.5 <=0.25 -0.7818441 1.5416948
-#> 10 J S 21 <=0.5 <=0.25 -1.0865856 1.8464363
+#> id amox cipr gent tobr amr_distance check_id_C
+#> 1 C S 26 >=8 8 0.3974553 0.0000000
+#> 2 G R 23 4 8 0.5614212 0.1639659
+#> 3 E I 31 2 8 0.2058131 0.1916421
+#> 4 F R 23 1 8 0.1354498 0.2620054
+#> 5 H I 31 4 <=1 -0.1640949 0.5615502
+#> 6 I I 18 >=8 4 -0.1717694 0.5692247
+#> 7 D R 28 >=8 8 1.0087361 0.6112809
+#> 8 B S 18 2 8 -0.4034429 0.8008982
+#> 9 A I 28 1 <=1 -0.7306638 1.1281191
+#> 10 J I 17 2 2 -0.8389046 1.2363598
if (require("dplyr")) {
# support for groups
example_isolates %>%
diff --git a/reference/microorganisms.codes.html b/reference/microorganisms.codes.html
index c6d746dd..9d4f398d 100644
--- a/reference/microorganisms.codes.html
+++ b/reference/microorganisms.codes.html
@@ -10,7 +10,7 @@
AMR (for R)
- 1.8.2.9080
+ 1.8.2.9081