diff --git a/src/tutorial_htrsim.Rmd b/src/tutorial_htrsim.Rmd
index 23fbe4a325adcc8d6ed5c8552decba10100a8415..8ddc0c5278709881116c40441fa15394635eea21 100644
--- a/src/tutorial_htrsim.Rmd
+++ b/src/tutorial_htrsim.Rmd
@@ -9,12 +9,13 @@ This is a tutorial for *htrsim* utilization
 ```{r required}
 library(data.table)
 library(tidyverse)
-#library("DESeq2")
+library(DESeq2)
 ```
 
 
 ```{r setworkdir}
-setwd("~/mydatalocal/counts_simulation/src/")
+# on berthollet
+setwd("/home2/aduvermy/counts_simulation/src/")
 ```
 
 
@@ -108,7 +109,7 @@ Next, plot your distribution of simulated counts per gene.</br>
 ```{r plot hist, echo = TRUE}
 
 data2plot <- htrs %>% reshape2::melt( ., id=c("name_gene"), variable.name = "Run")
-data2plot <- data2plot %>% group_by(name_gene) %>% mutate(mean_obs = mean(value)) %>% ungroup()
+data2plot <- data2plot %>% dplyr::group_by(name_gene) %>% dplyr::mutate(mean_obs = mean(value)) %>% dplyr::ungroup()
 
 figure = data2plot %>% ggplot(., aes(x=value)) +
   geom_histogram(fill= "grey", binwidth = 30) + 
@@ -327,11 +328,11 @@ We will mimic an existing design.
 
 ```{r message=FALSE, warning=FALSE}
 ## import mu(ij) params for each gene & each sample
-mu_params = readr::read_tsv(file="../../rna-seq_public_library_investigations/results/2022-03-03/estimate_mu.tsv")
+mu_params = readr::read_tsv(file="../../rna-seq_public_library_investigations/results/2022-03-03/estimate_mu.tsv", show_col_type=F)
 mu_params <- mu_params %>% select(., contains("rep1")) 
 
 ## import alpha(i) for each genes
-alpha_params = readr::read_tsv(file="../../rna-seq_public_library_investigations/results/2022-03-03/estimate_dispersion.tsv")
+alpha_params = readr::read_tsv(file="../../rna-seq_public_library_investigations/results/2022-03-03/estimate_dispersion.tsv", show_col_type=F)
 
 
 ## Defining sample names
@@ -366,6 +367,7 @@ genes <-  list(name = nameGene.set , alpha = alphaGene.set) %>% as.data.frame()
 source(file = "htrsim/setup_cntsGenerator.R")
 ## with mu dataframe
 setup.simulation <- setup_countGener(sample_names= samples$name , n_rep= samples$n_rep , gene_dispersion = genes$alpha, gene_names = genes$name, mu = mu_params)
+setup.simulation %>% head
 source(file= "htrsim/counts_generator.R" )
 htrs <- generate_counts(setup.simulation)
 ```