rsi <- random_rsi(10)
rsi
#> Class 'rsi'
-#> [1] S S R S R I S R I S
+#> [1] I I I R S I I I I I
mean_amr_distance(rsi)
-#> [1] -0.621059 -0.621059 1.449138 -0.621059 1.449138 -0.621059 -0.621059
-#> [8] 1.449138 -0.621059 -0.621059
+#> [1] -0.3162278 -0.3162278 -0.3162278 2.8460499 -0.3162278 -0.3162278
+#> [7] -0.3162278 -0.3162278 -0.3162278 -0.3162278
mic <- random_mic(10)
mic
#> Class 'mic'
-#> [1] 64 0.5 <=0.025 128 4 0.0625 256 2 128
-#> [10] 0.125
+#> [1] 4 >=64 0.001 1 0.0625 0.0625 0.25 0.0625 4 4
mean_amr_distance(mic)
-#> [1] 0.84443028 -0.55224804 -1.41458279 1.04395575 0.04632838 -1.15082446
-#> [7] 1.24348122 -0.15319709 1.04395575 -0.95129899
+#> [1] 0.7050535 1.5873138 -1.9341805 0.2639234 -0.6183369 -0.6183369
+#> [7] -0.1772067 -0.6183369 0.7050535 0.7050535
# equal to the Z-score of their log2:
(log2(mic) - mean(log2(mic))) / sd(log2(mic))
-#> [1] 0.84443028 -0.55224804 -1.41458279 1.04395575 0.04632838 -1.15082446
-#> [7] 1.24348122 -0.15319709 1.04395575 -0.95129899
+#> [1] 0.7050535 1.5873138 -1.9341805 0.2639234 -0.6183369 -0.6183369
+#> [7] -0.1772067 -0.6183369 0.7050535 0.7050535
disk <- random_disk(10)
disk
#> Class 'disk'
-#> [1] 31 19 25 45 43 45 10 42 38 47
+#> [1] 38 50 21 40 26 10 16 45 24 19
mean_amr_distance(disk)
-#> [1] -0.2747505 -1.2167523 -0.7457514 0.8242516 0.6672513 0.8242516
-#> [7] -1.9232536 0.5887511 0.2747505 0.9812518
+#> [1] 0.6768341 1.5693625 -0.5875812 0.8255888 -0.2156944 -1.4057323
+#> [7] -0.9594681 1.1974757 -0.3644491 -0.7363360
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 20 <=0.25 4
-#> 2 B R 25 1 2
-#> 3 C I 24 0.5 4
-#> 4 D S 17 2 >=8
-#> 5 E S 25 <=0.25 1
-#> 6 F R 28 >=4 0.25
-#> 7 G I 29 2 1
-#> 8 H I 22 1 0.5
-#> 9 I I 18 2 0.25
-#> 10 J I 21 0.5 1
+#> id amox cipr gent tobr
+#> 1 A I 30 8 2
+#> 2 B S 17 4 >=4
+#> 3 C R 19 8 >=4
+#> 4 D R 29 2 >=4
+#> 5 E I 19 8 <=1
+#> 6 F R 28 8 2
+#> 7 G R 26 8 >=4
+#> 8 H I 25 1 >=4
+#> 9 I R 27 4 >=4
+#> 10 J R 21 0.5 <=1
mean_amr_distance(y)
#> ℹ Calculating mean AMR distance based on columns "amox", "cipr", "gent" and
#> "tobr"
-#> [1] -0.39633734 0.72619085 0.03532415 0.11086821 -0.37841945 0.83757068
-#> [7] 0.41812023 -0.34726311 -0.56085146 -0.44520275
+#> [1] 0.09446764 -0.47291812 0.29008010 0.47684186 -0.78696988 0.47223165
+#> [7] 0.66233628 -0.39251526 0.54299934 -0.88655361
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
-#> 5 E S 25 <=0.25 1 -0.78135160
-#> 10 J I 21 0.5 1 -0.41647341
-#> 8 H I 22 1 0.5 -0.34520532
-#> 9 I I 18 2 0.25 -0.27393724
-#> 1 A S 20 <=0.25 4 -0.19413138
-#> 6 F R 28 >=4 0.25 0.09094095
-#> 3 C I 24 0.5 4 0.17074681
-#> 2 B R 25 1 2 0.24201490
-#> 7 G I 29 2 1 0.31328298
-#> 4 D S 17 2 >=8 1.19411331
+#> id amox cipr gent tobr amr_distance
+#> 10 J R 21 0.5 <=1 -1.83069295
+#> 5 E I 19 8 <=1 -0.45056183
+#> 8 H I 25 1 >=4 -0.29980604
+#> 4 D R 29 2 >=4 0.04522674
+#> 1 A I 30 8 2 0.14236523
+#> 6 F R 28 8 2 0.14236523
+#> 2 B S 17 4 >=4 0.39025951
+#> 9 I R 27 4 >=4 0.39025951
+#> 3 C R 19 8 >=4 0.73529229
+#> 7 G R 26 8 >=4 0.73529229
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 I 24 0.5 4 0.03532415 0.00000000
-#> 2 D S 17 2 >=8 0.11086821 0.07554406
-#> 3 H I 22 1 0.5 -0.34726311 0.38258727
-#> 4 G I 29 2 1 0.41812023 0.38279607
-#> 5 E S 25 <=0.25 1 -0.37841945 0.41374361
-#> 6 A S 20 <=0.25 4 -0.39633734 0.43166149
-#> 7 J I 21 0.5 1 -0.44520275 0.48052690
-#> 8 I I 18 2 0.25 -0.56085146 0.59617562
-#> 9 B R 25 1 2 0.72619085 0.69086670
-#> 10 F R 28 >=4 0.25 0.83757068 0.80224652
+#> id amox cipr gent tobr amr_distance check_id_C
+#> 1 C R 19 8 >=4 0.29008010 0.0000000
+#> 2 F R 28 8 2 0.47223165 0.1821516
+#> 3 D R 29 2 >=4 0.47684186 0.1867618
+#> 4 A I 30 8 2 0.09446764 0.1956125
+#> 5 I R 27 4 >=4 0.54299934 0.2529192
+#> 6 G R 26 8 >=4 0.66233628 0.3722562
+#> 7 H I 25 1 >=4 -0.39251526 0.6825954
+#> 8 B S 17 4 >=4 -0.47291812 0.7629982
+#> 9 E I 19 8 <=1 -0.78696988 1.0770500
+#> 10 J R 21 0.5 <=1 -0.88655361 1.1766337
if (require("dplyr")) {
# support for groups
example_isolates %>%
diff --git a/reference/microorganisms.codes.html b/reference/microorganisms.codes.html
index 481463f3..387e8329 100644
--- a/reference/microorganisms.codes.html
+++ b/reference/microorganisms.codes.html
@@ -10,7 +10,7 @@
AMR (for R)
- 1.8.2.9092
+ 1.8.2.9093