sir <- random_sir(10)
sir
#> Class 'sir'
-#> [1] R I S R R I I S I S
+#> [1] R S R I S I I S R S
mean_amr_distance(sir)
-#> [1] 1.449138 -0.621059 -0.621059 1.449138 1.449138 -0.621059 -0.621059
-#> [8] -0.621059 -0.621059 -0.621059
+#> [1] 1.449138 -0.621059 1.449138 -0.621059 -0.621059 -0.621059 -0.621059
+#> [8] -0.621059 1.449138 -0.621059
mic <- random_mic(10)
mic
#> Class 'mic'
-#> [1] 0.5 64 128 2 64 0.5 4 16 <=0.01 64
+#> [1] 0.005 1 0.125 2 <=0.001 <=0.001 1 2 16
+#> [10] 128
mean_amr_distance(mic)
-#> [1] -0.76841729 0.84415551 1.07452305 -0.30768220 0.84415551 -0.76841729
-#> [7] -0.07731466 0.38342042 -2.06857856 0.84415551
+#> [1] -1.0158675 0.3033189 -0.2144249 0.4759002 -1.4165887 -1.4165887
+#> [7] 0.3033189 0.4759002 0.9936440 1.5113878
# equal to the Z-score of their log2:
(log2(mic) - mean(log2(mic))) / sd(log2(mic))
-#> [1] -0.76841729 0.84415551 1.07452305 -0.30768220 0.84415551 -0.76841729
-#> [7] -0.07731466 0.38342042 -2.06857856 0.84415551
+#> [1] -1.0158675 0.3033189 -0.2144249 0.4759002 -1.4165887 -1.4165887
+#> [7] 0.3033189 0.4759002 0.9936440 1.5113878
disk <- random_disk(10)
disk
#> Class 'disk'
-#> [1] 33 13 32 20 13 17 12 43 11 48
+#> [1] 48 23 12 20 41 6 12 12 47 36
mean_amr_distance(disk)
-#> [1] 0.6399929 -0.8145365 0.5672665 -0.3054512 -0.8145365 -0.5236306
-#> [7] -0.8872630 1.3672577 -0.9599894 1.7308900
+#> [1] 1.4004215 -0.1695578 -0.8603487 -0.3579553 0.9608273 -1.2371437
+#> [7] -0.8603487 -0.8603487 1.3376224 0.6468315
y <- data.frame(
id = LETTERS[1:10],
@@ -251,22 +252,22 @@
tobr = random_mic(10, ab = "tobr", mo = "Escherichia coli")
)
y
-#> id amox cipr gent tobr
-#> 1 A S 29 2 4
-#> 2 B R 18 1 1
-#> 3 C S 22 1 1
-#> 4 D I 22 2 <=0.5
-#> 5 E S 29 4 1
-#> 6 F S 19 2 2
-#> 7 G R 19 2 <=0.5
-#> 8 H R 23 4 4
-#> 9 I S 22 2 4
-#> 10 J R 31 1 2
+#> id amox cipr gent tobr
+#> 1 A S 29 >=4 <=1
+#> 2 B R 24 <=0.25 2
+#> 3 C S 21 >=4 <=1
+#> 4 D I 29 0.5 2
+#> 5 E R 23 2 >=4
+#> 6 F S 20 2 <=1
+#> 7 G I 25 <=0.25 <=1
+#> 8 H I 23 >=4 >=4
+#> 9 I R 22 0.5 <=1
+#> 10 J S 17 1 <=1
mean_amr_distance(y)
#> ℹ Calculating mean AMR distance based on columns "amox", "cipr", "gent",
#> and "tobr"
-#> [1] 0.43964438 -0.43272533 -0.70168251 -0.57585273 0.35248847 -0.31125566
-#> [7] -0.25310412 0.93983415 0.06310433 0.47954902
+#> [1] 0.32544646 0.18797487 -0.20886404 0.15875482 0.88080476 -0.43003790
+#> [7] -0.55924901 0.51764065 -0.08768122 -0.78478940
y$amr_distance <- mean_amr_distance(y, where(is.mic))
#> Error in .subset(x, j): invalid subscript type 'list'
y[order(y$amr_distance), ]
@@ -282,17 +283,17 @@
}
#> 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 S 22 1 1 -0.70168251 0.0000000
-#> 2 D I 22 2 <=0.5 -0.57585273 0.1258298
-#> 3 B R 18 1 1 -0.43272533 0.2689572
-#> 4 F S 19 2 2 -0.31125566 0.3904268
-#> 5 G R 19 2 <=0.5 -0.25310412 0.4485784
-#> 6 I S 22 2 4 0.06310433 0.7647868
-#> 7 E S 29 4 1 0.35248847 1.0541710
-#> 8 A S 29 2 4 0.43964438 1.1413269
-#> 9 J R 31 1 2 0.47954902 1.1812315
-#> 10 H R 23 4 4 0.93983415 1.6415167
+#> id amox cipr gent tobr amr_distance check_id_C
+#> 1 C S 21 >=4 <=1 -0.20886404 0.0000000
+#> 2 I R 22 0.5 <=1 -0.08768122 0.1211828
+#> 3 F S 20 2 <=1 -0.43003790 0.2211739
+#> 4 G I 25 <=0.25 <=1 -0.55924901 0.3503850
+#> 5 D I 29 0.5 2 0.15875482 0.3676189
+#> 6 B R 24 <=0.25 2 0.18797487 0.3968389
+#> 7 A S 29 >=4 <=1 0.32544646 0.5343105
+#> 8 J S 17 1 <=1 -0.78478940 0.5759254
+#> 9 H I 23 >=4 >=4 0.51764065 0.7265047
+#> 10 E R 23 2 >=4 0.88080476 1.0896688
if (require("dplyr")) {
# support for groups
example_isolates %>%
diff --git a/reference/microorganisms.codes.html b/reference/microorganisms.codes.html
index 63fe948f..88f97f30 100644
--- a/reference/microorganisms.codes.html
+++ b/reference/microorganisms.codes.html
@@ -1,5 +1,5 @@
-Data Set with 4 942 Common Microorganism Codes — microorganisms.codes • AMR (for R)Data Set with 4 946 Common Microorganism Codes — microorganisms.codes • AMR (for R)
@@ -10,7 +10,7 @@
AMR (for R)
- 2.0.0.9025
+ 2.0.0.9026