Find Top5 min and max values per group in dataframe (determine min and max differentially expressed genes)

In a dataframe of differential expression results, find the 5 genes per group that are maximally and minimally regulated (= highest and lowest log fold change).
My solution with mutate and slice_max/min somehow wont work.

example data

set.seed(47)
gene_creator <- paste("gene",1:100,sep="")
genes = sample(gene_creator,8)

dex_A <- data.frame(
  gene = genes,
  group = "group_A",
  logFC = sample(c(-5:5), replace=T, size=8),
  FDR = sample(c(0.01,1), replace=T, size=8)
)

dex_B <- data.frame(
  gene = genes,
  group = "group_B",
  logFC = sample(c(-5:5), replace=T, size=8),
  FDR = sample(c(0.01,1), replace=T, size=8)
)

dex_df <- rbind(dex_A, dex_B)

solution (not working)

library(tidyverse)
dex_df %>%
  filter(FDR < 0.05) %>%
  group_by(group) %>%
  mutate(
    top5 = slice_max(logFC, n = 5),
    min5 = slice_min(logFC, n = 5))

You cannot use slice_max() or slice_min() directly with mutate. You have to use them separately and row bind them, i.e.

bind_rows(dex_df %>%
            filter(FDR < 0.05) %>%
            group_by(group) %>%
            slice_max(logFC, n = 5) %>%
            mutate(rank = "top5"),
          dex_df %>%
            filter(FDR < 0.05) %>%
            group_by(group) %>%
            slice_min(logFC, n = 5) %>%
            mutate(rank = "min5"))