disable progress bar in vignette articles to avoid printing issues

vignettes/rbioapi_do_enrich.Rmd

@@ -131,7 +131,8 @@ While the only required argument of `rba_enrichr()` function is `gene_list`, her
 enrichr_enrich <- rba_enrichr(
   gene_list = covid_critical,
   organism = "human",
-  gene_set_library = "KEGG_2021_Human"
+  gene_set_library = "KEGG_2021_Human",
+  progress_bar = FALSE # to avoid printing issues in the vignette
 )
 ```
 
@@ -162,7 +163,8 @@ In the `gene_set_library` parameter, you can also provide multiple gene set libr
 enrichr_enrich_kegg <- rba_enrichr(
   gene_list = covid_critical,
   gene_set_library = "kegg",
-  regex_library_name = TRUE # default value
+  regex_library_name = TRUE, # default value
+  progress_bar = FALSE # to avoid printing issues in the vignette
 )
 ```
 
@@ -445,7 +447,7 @@ In addition to a data frame, you can also get a plot summarizing the enrichment
 
 
 ```{r string_enrichment_plot, fig.show='hide'}
-graph_3 <- rba_string_enrichment_image(
+enrich_plot <- rba_string_enrichment_image(
   ids = covid_critical,
   species = 9606,
   category = "KEGG",
@@ -456,8 +458,8 @@ graph_3 <- rba_string_enrichment_image(
 ```
 
 ```{r string_enrichment_plot_image, echo=FALSE, fig.cap="Visualization of enrichment analysis results", fig.align='center', fig.width=7}
-if (is.array(graph_3)) {
-  grid::grid.raster(graph_3, just = "center")
+if (is.array(enrich_plot)) {
+  grid::grid.raster(enrich_plot, just = "center")
 } else {
   print("Vignette building failed. It is probably because the web service was down during the building.")
 }

vignettes/rbioapi_enrichr.Rmd

@@ -110,7 +110,8 @@ Sys.sleep(3)
 # Request the enrichment analysis by a specific library
 results_msig_hallmark <- rba_enrichr(
   gene_list = genes,
-  gene_set_library = "MSigDB_Hallmark_2020"
+  gene_set_library = "MSigDB_Hallmark_2020",
+  progress_bar = FALSE # to avoid printing issues in the vignette
 )
 ```
 
@@ -143,7 +144,8 @@ Sys.sleep(3)
 results_msig <- rba_enrichr(
   gene_list = genes,
   gene_set_library = "msig",
-  regex_library_name = TRUE
+  regex_library_name = TRUE,
+  progress_bar = FALSE # to avoid printing issues in the vignette
 )
 
 # You can drop `regex_library_name = TRUE`, as it is TRUE by default.
@@ -258,6 +260,9 @@ results_msig <- rba_enrichr(
 If you choose to follow the step-by-step approach, please note that Enrichr relies on an API back-end called [speedrichr](https://github.com/MaayanLab/speedrichr) to handle analysis with a background gene list. Therefore, when performing an analysis with background gene list, you must explicitly upload the target gene list to speedrichr. . Later steps will automatically interact with speedrichr as long as the relevant parameters for the background genes are specified.
 
 ```{r background_gene_list_approach2, eval=FALSE}
+
+# Assume we have the background genes in the variable my_background_genes
+
 # Create a vector with our genes' NCBI IDs
 genes <- c(
   "p53", "BRCA1", "cdk2", "Q99835", "CDC42","CDK1","KIF23","PLK1",