rsi <- random_rsi(10)
rsi
#> Class 'rsi'
-#> [1] S R R R I I I R S R
+#> [1] S I S R S I S S S S
mean_amr_distance(rsi)
-#> [1] -0.9486833 0.9486833 0.9486833 0.9486833 -0.9486833 -0.9486833
-#> [7] -0.9486833 0.9486833 -0.9486833 0.9486833
+#> [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] 2 0.025 >=128 0.025 >=128 16 4 >=128 8 0.025
+#> [1] 0.005 32 >=64 0.001 32 0.005 >=64 0.001 >=64 32
mean_amr_distance(mic)
-#> [1] -0.09761619 -1.32347254 1.06581655 -1.32347254 1.06581655 0.48410018
-#> [7] 0.09628927 1.06581655 0.29019472 -1.32347254
+#> [1] -0.9977554 0.7020018 0.8364352 -1.3099002 0.7020018 -0.9977554
+#> [7] 0.8364352 -1.3099002 0.8364352 0.7020018
# equal to the Z-score of their log2:
(log2(mic) - mean(log2(mic))) / sd(log2(mic))
-#> [1] -0.09761619 -1.32347254 1.06581655 -1.32347254 1.06581655 0.48410018
-#> [7] 0.09628927 1.06581655 0.29019472 -1.32347254
+#> [1] -0.9977554 0.7020018 0.8364352 -1.3099002 0.7020018 -0.9977554
+#> [7] 0.8364352 -1.3099002 0.8364352 0.7020018
disk <- random_disk(10)
disk
#> Class 'disk'
-#> [1] 44 29 31 8 26 23 36 34 41 46
+#> [1] 43 13 6 50 43 19 14 23 8 44
mean_amr_distance(disk)
-#> [1] 1.0822909 -0.2483946 -0.0709699 -2.1113544 -0.5145317 -0.7806689
-#> [7] 0.3725920 0.1951672 0.8161538 1.2597157
+#> [1] 0.9878564 -0.7867359 -1.2008074 1.4019279 0.9878564 -0.4318175
+#> [7] -0.7275828 -0.1952051 -1.0825013 1.0470094
y <- data.frame(
id = LETTERS[1:10],
@@ -225,35 +225,35 @@
)
y
#> id amox cipr gent tobr
-#> 1 A I 27 0.5 4
-#> 2 B I 27 2 2
-#> 3 C S 20 >=8 8
-#> 4 D I 27 4 2
-#> 5 E I 22 4 4
-#> 6 F S 31 2 <=1
-#> 7 G S 26 1 >=16
-#> 8 H R 21 4 <=1
-#> 9 I R 31 4 2
-#> 10 J S 30 4 4
+#> 1 A I 22 4 2
+#> 2 B I 24 0.5 2
+#> 3 C R 30 2 1
+#> 4 D S 29 0.5 1
+#> 5 E I 30 4 2
+#> 6 F R 19 0.25 4
+#> 7 G I 26 4 4
+#> 8 H S 22 2 2
+#> 9 I S 29 2 1
+#> 10 J I 28 0.5 1
mean_amr_distance(y)
#> ℹ Calculating mean AMR distance based on columns "amox", "cipr", "gent" and
#> "tobr"
-#> [1] -0.50096961 -0.27264058 0.11352599 -0.05965490 -0.17279077 -0.22166036
-#> [7] 0.04514514 -0.03730406 0.78189474 0.32445439
+#> [1] -0.03769893 -0.40858317 0.58133901 -0.40733070 0.47139759 0.01703862
+#> [7] 0.53378217 -0.20375172 -0.07522511 -0.47096776
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 27 0.5 4 -0.8642174
-#> 6 F S 31 2 <=1 -0.8028441
-#> 2 B I 27 2 2 -0.4075594
-#> 8 H R 21 4 <=1 -0.3768727
-#> 4 D I 27 4 2 0.0184120
-#> 9 I R 31 4 2 0.0184120
-#> 7 G S 26 1 >=16 0.3523234
-#> 5 E I 22 4 4 0.4136967
-#> 10 J S 30 4 4 0.4136967
-#> 3 C S 20 >=8 8 1.2349528
+#> 4 D S 29 0.5 1 -0.97204037
+#> 10 J I 28 0.5 1 -0.97204037
+#> 2 B I 24 0.5 2 -0.33817468
+#> 3 C R 30 2 1 -0.30782920
+#> 9 I S 29 2 1 -0.30782920
+#> 6 F R 19 0.25 4 -0.03641457
+#> 8 H S 22 2 2 0.32603649
+#> 1 A I 22 4 2 0.65814207
+#> 5 E I 30 4 2 0.65814207
+#> 7 G I 26 4 4 1.29200776
if (require("dplyr")) {
y %>%
@@ -266,16 +266,16 @@
#> 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 S 20 >=8 8 0.11352599 0.00000000
-#> 2 G S 26 1 >=16 0.04514514 0.06838084
-#> 3 H R 21 4 <=1 -0.03730406 0.15083004
-#> 4 D I 27 4 2 -0.05965490 0.17318088
-#> 5 J S 30 4 4 0.32445439 0.21092841
-#> 6 E I 22 4 4 -0.17279077 0.28631675
-#> 7 F S 31 2 <=1 -0.22166036 0.33518634
-#> 8 B I 27 2 2 -0.27264058 0.38616657
-#> 9 A I 27 0.5 4 -0.50096961 0.61449559
-#> 10 I R 31 4 2 0.78189474 0.66836876
+#> 1 C R 30 2 1 0.58133901 0.00000000
+#> 2 G I 26 4 4 0.53378217 0.04755684
+#> 3 E I 30 4 2 0.47139759 0.10994142
+#> 4 F R 19 0.25 4 0.01703862 0.56430040
+#> 5 A I 22 4 2 -0.03769893 0.61903794
+#> 6 I S 29 2 1 -0.07522511 0.65656413
+#> 7 H S 22 2 2 -0.20375172 0.78509073
+#> 8 D S 29 0.5 1 -0.40733070 0.98866971
+#> 9 B I 24 0.5 2 -0.40858317 0.98992219
+#> 10 J I 28 0.5 1 -0.47096776 1.05230677
if (require("dplyr")) {
# support for groups
example_isolates %>%
diff --git a/reference/microorganisms.codes.html b/reference/microorganisms.codes.html
index 0f81adc2..be86a5f2 100644
--- a/reference/microorganisms.codes.html
+++ b/reference/microorganisms.codes.html
@@ -10,7 +10,7 @@
AMR (for R)
- 1.8.2.9086
+ 1.8.2.9088