diff --git a/DESCRIPTION b/DESCRIPTION
index eee99559..1301addb 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
Package: AMR
-Version: 1.0.1.9008
-Date: 2020-04-14
+Version: 1.0.1.9009
+Date: 2020-04-15
Title: Antimicrobial Resistance Analysis
Authors@R: c(
person(role = c("aut", "cre"),
diff --git a/NEWS.md b/NEWS.md
index 2c44e8fc..17aa8447 100755
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,5 +1,5 @@
-# AMR 1.0.1.9008
-## Last updated: 14-Apr-2020
+# AMR 1.0.1.9009
+## Last updated: 15-Apr-2020
### New
* Support for easy principal component analysis for AMR, using the new `pca()` function
diff --git a/R/first_isolate.R b/R/first_isolate.R
index 049ffd6b..1657b94f 100755
--- a/R/first_isolate.R
+++ b/R/first_isolate.R
@@ -90,18 +90,8 @@
#' library(dplyr)
#' # Filter on first isolates:
#' example_isolates %>%
-#' mutate(first_isolate = first_isolate(.,
-#' col_date = "date",
-#' col_patient_id = "patient_id",
-#' col_mo = "mo")) %>%
+#' mutate(first_isolate = first_isolate(.)) %>%
#' filter(first_isolate == TRUE)
-#'
-#' # Which can be shortened to:
-#' example_isolates %>%
-#' filter_first_isolate()
-#' # or for first weighted isolates:
-#' example_isolates %>%
-#' filter_first_weighted_isolate()
#'
#' # Now let's see if first isolates matter:
#' A <- example_isolates %>%
@@ -116,14 +106,22 @@
#' resistance = resistance(GEN)) # gentamicin resistance
#'
#' # Have a look at A and B.
-#' # B is more reliable because every isolate is only counted once.
-#' # Gentamicin resitance in hospital D appears to be 3.1% higher than
+#' # B is more reliable because every isolate is counted only once.
+#' # Gentamicin resitance in hospital D appears to be 3.7% higher than
#' # when you (erroneously) would have used all isolates for analysis.
#'
#'
#' ## OTHER EXAMPLES:
#'
#' \dontrun{
+#'
+#' # Short-hand versions:
+#' example_isolates %>%
+#' filter_first_isolate()
+#'
+#' example_isolates %>%
+#' filter_first_weighted_isolate()
+#'
#'
#' # set key antibiotics to a new variable
#' x$keyab <- key_antibiotics(x)
diff --git a/docs/404.html b/docs/404.html
index 0722fc9f..fa9c9687 100644
--- a/docs/404.html
+++ b/docs/404.html
@@ -81,7 +81,7 @@
AMR (for R)
- 1.0.1.9008
+ 1.0.1.9009
diff --git a/docs/LICENSE-text.html b/docs/LICENSE-text.html
index fdfe0273..f5bcbc64 100644
--- a/docs/LICENSE-text.html
+++ b/docs/LICENSE-text.html
@@ -81,7 +81,7 @@
AMR (for R)
- 1.0.1.9008
+ 1.0.1.9009
diff --git a/docs/articles/PCA.html b/docs/articles/PCA.html
index c9056aa7..1e02fa61 100644
--- a/docs/articles/PCA.html
+++ b/docs/articles/PCA.html
@@ -39,7 +39,7 @@
AMR (for R)
- 1.0.1.9005
+ 1.0.1.9009
@@ -186,7 +186,7 @@
How to conduct principal component analysis (PCA) for AMR
Matthijs S. Berends
- 13 April 2020
+ 15 April 2020
Source: vignettes/PCA.Rmd
PCA.Rmd
diff --git a/docs/articles/index.html b/docs/articles/index.html
index 60197a70..dd8f86bd 100644
--- a/docs/articles/index.html
+++ b/docs/articles/index.html
@@ -81,7 +81,7 @@
AMR (for R)
- 1.0.1.9008
+ 1.0.1.9009
diff --git a/docs/authors.html b/docs/authors.html
index 64922785..3d54f2f3 100644
--- a/docs/authors.html
+++ b/docs/authors.html
@@ -81,7 +81,7 @@
AMR (for R)
- 1.0.1.9008
+ 1.0.1.9009
diff --git a/docs/countries.png b/docs/countries.png
index 62084e3f..e3ac90a6 100644
Binary files a/docs/countries.png and b/docs/countries.png differ
diff --git a/docs/countries_large.png b/docs/countries_large.png
index 1756232f..80ea0809 100644
Binary files a/docs/countries_large.png and b/docs/countries_large.png differ
diff --git a/docs/index.html b/docs/index.html
index f1491e7a..9246dec8 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -43,7 +43,7 @@
AMR (for R)
- 1.0.1.9008
+ 1.0.1.9009
diff --git a/docs/news/index.html b/docs/news/index.html
index a88c0d8d..7fba063c 100644
--- a/docs/news/index.html
+++ b/docs/news/index.html
@@ -81,7 +81,7 @@
AMR (for R)
- 1.0.1.9008
+ 1.0.1.9009
@@ -229,13 +229,13 @@
Source: NEWS.md
-
-
diff --git a/docs/reference/microorganisms.codes.html b/docs/reference/microorganisms.codes.html
index 5ee6783f..e3440280 100644
--- a/docs/reference/microorganisms.codes.html
+++ b/docs/reference/microorganisms.codes.html
@@ -82,7 +82,7 @@
AMR (for R)
- 1.0.1.9005
+ 1.0.1.9009
diff --git a/docs/reference/microorganisms.html b/docs/reference/microorganisms.html
index ffec4fb9..dcb1c823 100644
--- a/docs/reference/microorganisms.html
+++ b/docs/reference/microorganisms.html
@@ -82,7 +82,7 @@
AMR (for R)
- 1.0.1.9008
+ 1.0.1.9009
diff --git a/docs/reference/microorganisms.old.html b/docs/reference/microorganisms.old.html
index 61523f8a..1eaf5624 100644
--- a/docs/reference/microorganisms.old.html
+++ b/docs/reference/microorganisms.old.html
@@ -82,7 +82,7 @@
AMR (for R)
- 1.0.1.9005
+ 1.0.1.9009
diff --git a/docs/reference/rsi_translation.html b/docs/reference/rsi_translation.html
index 79c79b37..bc95c3c4 100644
--- a/docs/reference/rsi_translation.html
+++ b/docs/reference/rsi_translation.html
@@ -82,7 +82,7 @@
AMR (for R)
- 1.0.1.9006
+ 1.0.1.9009
diff --git a/man/first_isolate.Rd b/man/first_isolate.Rd
index 8f07ec63..b77c5262 100755
--- a/man/first_isolate.Rd
+++ b/man/first_isolate.Rd
@@ -145,19 +145,9 @@ On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://
library(dplyr)
# Filter on first isolates:
example_isolates \%>\%
- mutate(first_isolate = first_isolate(.,
- col_date = "date",
- col_patient_id = "patient_id",
- col_mo = "mo")) \%>\%
+ mutate(first_isolate = first_isolate(.)) \%>\%
filter(first_isolate == TRUE)
-# Which can be shortened to:
-example_isolates \%>\%
- filter_first_isolate()
-# or for first weighted isolates:
-example_isolates \%>\%
- filter_first_weighted_isolate()
-
# Now let's see if first isolates matter:
A <- example_isolates \%>\%
group_by(hospital_id) \%>\%
@@ -171,8 +161,8 @@ B <- example_isolates \%>\%
resistance = resistance(GEN)) # gentamicin resistance
# Have a look at A and B.
-# B is more reliable because every isolate is only counted once.
-# Gentamicin resitance in hospital D appears to be 3.1\% higher than
+# B is more reliable because every isolate is counted only once.
+# Gentamicin resitance in hospital D appears to be 3.7\% higher than
# when you (erroneously) would have used all isolates for analysis.
@@ -180,6 +170,14 @@ B <- example_isolates \%>\%
\dontrun{
+# Short-hand versions:
+example_isolates \%>\%
+ filter_first_isolate()
+
+example_isolates \%>\%
+ filter_first_weighted_isolate()
+
+
# set key antibiotics to a new variable
x$keyab <- key_antibiotics(x)
diff --git a/pkgdown/logos/countries.png b/pkgdown/logos/countries.png
index 62084e3f..e3ac90a6 100644
Binary files a/pkgdown/logos/countries.png and b/pkgdown/logos/countries.png differ
diff --git a/pkgdown/logos/countries_large.png b/pkgdown/logos/countries_large.png
index 1756232f..80ea0809 100644
Binary files a/pkgdown/logos/countries_large.png and b/pkgdown/logos/countries_large.png differ