diff --git a/DESCRIPTION b/DESCRIPTION
index 4d86b4b..59d1564 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: DetectoR
 Title: Stay Safe; Don't Miss Any Adverse-Event Signal
-Version: 3.0.1.9006
+Version: 3.0.1.9007
 Authors@R: c(
     person("Carlos", "Fernandez-Escobar", , "carlos.fernandez4.ext@bayer.com", role = c("aut", "cre")),
     person("Steffen", "Jeske", role = "aut"),
diff --git a/R/mod_calculate.R b/R/mod_calculate.R
index 2741b5c..c60d6c2 100644
--- a/R/mod_calculate.R
+++ b/R/mod_calculate.R
@@ -313,7 +313,8 @@ mod_calculate_server <- function(id, r, calculate_mode) {
       } else if (input$stratified_by == "None") {
         choices <- list(
           "Two sided" = "two.sided",
-          "One sided" = "less"
+          "One sided (favours comparator)" = "greater",
+          "One sided (favours verum)" = "less"
         )
       }
       shiny::updateSelectInput(
diff --git a/R/mod_calculate_fct_data.R b/R/mod_calculate_fct_data.R
index 4bfce16..1d86fbd 100644
--- a/R/mod_calculate_fct_data.R
+++ b/R/mod_calculate_fct_data.R
@@ -39,7 +39,7 @@ calculate_results <- function(
   adjustment = c("FDR", "DFDR"),
   order_by = c("p-value", "effect"),
   study_strat = "None",
-  alternative = c("two.sided", "less"),
+  alternative = c("two.sided", "less", "greater"),
   alpha = 0.05,
   filter = c("no_method", "one_percent", "min"),
   frequency_measure = c("proportions", "incidence rates"),
@@ -232,7 +232,7 @@ filter_empty_variable <- function(data, variable) {
 #' @param method A character, the method of filtering: "no_method",
 #'  "one_percent" or "min". "min" calls find_min_event()
 #' @param alternative A character describing the alternative hypothesis for
-#'  "min" method: "two.sided" or "less" (one-sided)
+#'  "min" method: "two.sided", "less" or "greater" (one-sided)
 #' @param alpha Numeric, alpha level of the test for "min" method.
 #'
 #' @returns A dataframe of filtered adverse events.
@@ -241,7 +241,7 @@ filter_minimum_aes <- function(
   variable,
   big_n,
   method = c("no_method", "one_percent", "min"),
-  alternative = c("two.sided", "less"),
+  alternative = c("two.sided", "less", "greater"),
   alpha
 ) {
   filter <- match.arg(method)
diff --git a/R/mod_calculate_fct_effect.R b/R/mod_calculate_fct_effect.R
index 8ece8b9..15b37e3 100644
--- a/R/mod_calculate_fct_effect.R
+++ b/R/mod_calculate_fct_effect.R
@@ -320,8 +320,11 @@ get_rr <- function(
 #'
 #' @returns A numeric vector with p-values
 get_fisher_p_value <- function(a, b, c, d, alternative) {
-  stats::fisher.test(
-    matrix(c(a, b, c, d), nrow = 2),
+  #TODO: remove
+  matrix <- matrix(c(a, b, c, d), nrow = 2)
+  out <- stats::fisher.test(
+    matrix,
     alternative = alternative
-  )$p.value
+  )
+  out$p.value
 }
diff --git a/R/utils_helpers.R b/R/utils_helpers.R
index ca921c3..2abc412 100644
--- a/R/utils_helpers.R
+++ b/R/utils_helpers.R
@@ -10,10 +10,11 @@
 find_min_event <- function(
   n1,
   n2,
-  alternative = c("two.sided", "less"),
+  alternative = c("two.sided", "less", "greater"),
   alpha = 0.05
 ) {
   alternative <- match.arg(alternative)
+  alternative <- if (alternative == "greater") "less" else alternative
   # Create a numeric vectors of events, to try which yields significant results
   if (n1 < 1000) {
     x1 <- seq(1, round(0.1 * n1, 0), 1)
diff --git a/man/calculate_results.Rd b/man/calculate_results.Rd
index f0fab8c..379c164 100644
--- a/man/calculate_results.Rd
+++ b/man/calculate_results.Rd
@@ -12,7 +12,7 @@ calculate_results(
   adjustment = c("FDR", "DFDR"),
   order_by = c("p-value", "effect"),
   study_strat = "None",
-  alternative = c("two.sided", "less"),
+  alternative = c("two.sided", "less", "greater"),
   alpha = 0.05,
   filter = c("no_method", "one_percent", "min"),
   frequency_measure = c("proportions", "incidence rates"),
diff --git a/man/filter_minimum_aes.Rd b/man/filter_minimum_aes.Rd
index 794a8ca..c7c2011 100644
--- a/man/filter_minimum_aes.Rd
+++ b/man/filter_minimum_aes.Rd
@@ -9,7 +9,7 @@ filter_minimum_aes(
   variable,
   big_n,
   method = c("no_method", "one_percent", "min"),
-  alternative = c("two.sided", "less"),
+  alternative = c("two.sided", "less", "greater"),
   alpha
 )
 }
@@ -25,7 +25,7 @@ treatment arm.}
 "one_percent" or "min". "min" calls find_min_event()}
 
 \item{alternative}{A character describing the alternative hypothesis for
-"min" method: "two.sided" or "less" (one-sided)}
+"min" method: "two.sided", "less" or "greater" (one-sided)}
 
 \item{alpha}{Numeric, alpha level of the test for "min" method.}
 }
diff --git a/man/find_min_event.Rd b/man/find_min_event.Rd
index ec005b4..38a5fd3 100644
--- a/man/find_min_event.Rd
+++ b/man/find_min_event.Rd
@@ -4,7 +4,12 @@
 \alias{find_min_event}
 \title{Calculate the minimum number of events in verum}
 \usage{
-find_min_event(n1, n2, alternative = c("two.sided", "less"), alpha = 0.05)
+find_min_event(
+  n1,
+  n2,
+  alternative = c("two.sided", "less", "greater"),
+  alpha = 0.05
+)
 }
 \arguments{
 \item{n1}{Number of patients in Verum}