fix: remove old config.yml

closes #33
halbritter-lab · May 14, 2024 · 1ac546c · 1ac546c
1 parent e5c6f79
commit 1ac546c
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Showing 4 changed files with 4 additions and 19 deletions.
diff --git a/.github/workflows/gh-pages.yml b/.github/workflows/gh-pages.yml
@@ -22,7 +22,6 @@ on:
 env:
     DRAWIO_DISABLE_UPDATE: true
     DISPLAY: :99.0
-    CONFIG_FILE: config.yml
     R_ENVIRONMENT: github
 
 jobs:

diff --git a/config.yml b/config.yml
diff --git a/documentation/01-analyses-tables.Rmd b/documentation/01-analyses-tables.Rmd
@@ -34,7 +34,6 @@ datatable(merge_analyses_sources_reformat,
         )
 ```
 
-
 ## Result table: PanelApp
 
 This table shows results of the first analysis searching kidney disease associated genes from the PanelApp project in the UK and Australia.
@@ -54,7 +53,6 @@ datatable(PanelApp_genes_reformat,
           escape = FALSE) # this argument renders the links as HTML
 ```
 
-
 ## Result table: Literature
 
 This table shows results of the second analysis searching kidney disease associated genes from various publications.
@@ -74,7 +72,6 @@ datatable(Literature_genes_reformat,
           escape = FALSE) # this argument renders the links as HTML
 ```
 
-
 ## Result table: Diagnostic panels
 
 This table shows results of the third analysis searching kidney disease associated genes from clinical diagnostic panels for kidney disease.
@@ -94,7 +91,6 @@ datatable(DiagnosticPanels_genes_reformat,
           escape = FALSE) # this argument renders the links as HTML
 ```
 
-
 ## Result table: HPO in rare disease databases
 
 This table shows results of the fourth analysis searching kidney disease associated genes from a Human Phenotype Ontology (HPO)-based search in rare disease databases (OMIM, Orphanet).
@@ -114,7 +110,6 @@ datatable(HPO_genes_reformat,
           escape = FALSE) # this argument renders the links as HTML
 ```
 
-
 ## Result table: PubTator
 
 This table shows results of the fifth analysis searching kidney disease associated genes from a PubTator API-based automated literature extraction from PubMed.
@@ -132,4 +127,4 @@ PubTator_genes_reformat <- PubTator_genes %>%
 datatable(PubTator_genes_reformat,
           filter = 'top', # this argument positions the filtering input at the top of the table
           escape = FALSE) # this argument renders the links as HTML
-```
+```
diff --git a/documentation/02-analyses-plots.Rmd b/documentation/02-analyses-plots.Rmd
@@ -21,7 +21,6 @@ ComplexUpset::upset(merge_analyses_sources_with_evidence, analyses,
 height_ratio = 0.5, width_ratio = 0.3, )
 ```
 
-
 ## Bar plot of PanelApp results
 
 > Below you can see a Bar plot of the PanelApp analysis.  
@@ -47,14 +46,13 @@ PanelApp_genes_counts_plot <- ggplot(PanelApp_genes_counts , aes(x = source_coun
 ggplotly(PanelApp_genes_counts_plot)
 ```
 
-
 ## Bar plot of Literature results
 
 > Below you can see a Bar plot of the Literature analysis.  
 
 We identified Genes associated with kidney disease in a systematic Literature search using the following search query:  
-      *(1)	"Kidney"[Mesh] OR "Kidney Diseases"[Mesh] OR kidney OR renal* AND  
-      *(2)	"Genetic Structures"[Mesh] OR "Genes"[Mesh] OR genetic test OR gene panel OR gene panels OR multigene panel* OR targeted panel*  
+      *(1) "Kidney"[Mesh] OR "Kidney Diseases"[Mesh] OR kidney OR renal* AND  
+      *(2) "Genetic Structures"[Mesh] OR "Genes"[Mesh] OR genetic test OR gene panel OR gene panels OR multigene panel* OR targeted panel*  
 
 - The y axis shows the number of Genes in different publications, which is also visualized by the height of the bars.  
 - The x axis displays the number of publications (source_count), i.e. in how many different publications a single Gene occurred.  
@@ -75,7 +73,6 @@ Literature_genes_counts_plot <- ggplot(Literature_genes_counts , aes(x = source_
 ggplotly(Literature_genes_counts_plot)
 ```
 
-
 ## Bar plot of Diagnostic panels results
 
 > Below you can see a Bar plot of the Diagnostic panels analysis.  
@@ -101,7 +98,6 @@ DiagnosticPanels_genes_counts_plot <- ggplot(DiagnosticPanels_genes_counts , aes
 ggplotly(DiagnosticPanels_genes_counts_plot)
 ```
 
-
 ## Bar plot of HPO in rare disease databases results
 
 > Below you can see a Bar plot of the HPO-term based query in rare disease databases (OMIM, Orphanet).  
@@ -129,7 +125,6 @@ HPO_genes_counts_plot <- ggplot(HPO_genes_counts , aes(x = source_count, y = num
 ggplotly(HPO_genes_counts_plot)
 ```
 
-
 ## Bar plot of PubTator results
 
 > Below you can see a Bar plot of the PubTator analysis.  
@@ -153,4 +148,4 @@ PubTator_genes_counts_plot <- ggplot(PubTator_genes_counts , aes(x = source_coun
 
 # convert to interactive using ggplotly
 ggplotly(PubTator_genes_counts_plot)
-```
+```