links now in question marks to precise location in docs

program/shinyApp/helpfiles/DataSelection_DataUploadFileInput.md

@@ -1,6 +1,7 @@
 ### Data Upload via File Input
 
 ***
+💡 **Tip**: For more detailed information, please visit <a href="https://icb-dcm.github.io/cOmicsArt/interface-details/required-data-input.html" target="_blank">here</a>.
 
 With `Data upload` you can upload your data to the server via explicit csv files.<br>
 The files must be in the following format:<br>

program/shinyApp/helpfiles/DataSelection_MetaData.md

@@ -1,6 +1,7 @@
 ### Data Upload via File Input + Meta Data Sheet
 
 ***
+💡 **Tip**: For more detailed information, please visit <a href="https://icb-dcm.github.io/cOmicsArt/interface-details/required-data-input.html#starting-with-a-single-table-and-a-metadatasheet-" target="_blank">here</a>.
 
 With `Data upload` you can upload your data to the server via explicit csv files.<br>
 The files must be in the following format:<br>

program/shinyApp/helpfiles/DataSelection_RowSelection.md

@@ -1,6 +1,7 @@
 ### Data Selection by Columns and Rows
 
 ***
+💡 **Tip**: For more detailed information, please visit <a href="https://icb-dcm.github.io/cOmicsArt/interface-details/selection.html#row-selection---biochemical-entities" target="_blank">here</a>.
 
 With `Row selection` you can choose the entities (e.g. genes) you want to include in the 
 analysis.

program/shinyApp/helpfiles/DataSelection_SummarizedExp.md

@@ -1,6 +1,7 @@
 ### Data Upload via Precompiled Data
 
 ***
+💡 **Tip**: For more detailed information, please visit <a href="https://icb-dcm.github.io/cOmicsArt/interface-details/required-data-input.html#starting-with-an-rds-object" target="_blank">here</a>.
 
 With this option, you can upload previously used data. This allows you to upload 
 everything at once. Additionally, you can upload results from previous analyses. It is 

program/shinyApp/helpfiles/DataSelection_UploadInspection.md

@@ -1,6 +1,7 @@
 ### Data Quality Check - Visual Inspection
 
 ***
+💡 **Tip**: For more detailed information, please visit <a href="https://icb-dcm.github.io/cOmicsArt/interface-details/selection.html#file-input-%EF%B8%8F" target="_blank">here</a>.
 
 Using the `Upload visual inspection` tab, you can see the uploaded data and perform a 
 data quality check.

program/shinyApp/helpfiles/EA_GeneSets.md

@@ -1,5 +1,7 @@
 ## Gene Sets for Enrichment Analysis
 
+***
+
 You can choose a variety of gene sets for enrichment analysis. Here you find a 
 description of the gene sets. The information was taken from the
 [MSigDB database](https://www.gsea-msigdb.org/gsea/msigdb/collections.jsp), where you 

program/shinyApp/helpfiles/EA_Options.md

@@ -1,6 +1,8 @@
 ## Enrichment Analysis Options
 
 ---
+💡 **Tip**: For more detailed information, please visit <a href="https://icb-dcm.github.io/cOmicsArt/interface-details/enrichment-analysis.html" target="_blank">here</a>.
+
 In cOmicsArt you can do either a gene set enrichment analysis or an over-representation analysis. The options for both analyses are described below.
 For more details read here on
 [Gene Set Enrichment Analysis](https://www.pnas.org/doi/abs/10.1073/pnas.0506580102) 

program/shinyApp/helpfiles/Heatmap_Aesthetics.md

@@ -1,6 +1,8 @@
 ## Heatmap Aesthetics Options
 
 ---
+💡 **Tip**: For more detailed information, please visit <a href="https://icb-dcm.github.io/cOmicsArt/interface-details/heatmap.html#aesthetics-options" target="_blank">here</a>.
+
 **1. Choose Variable to Color the Samples After:**
 
 - **Description:**

program/shinyApp/helpfiles/Heatmap_FurtherOptions.md

@@ -1,6 +1,8 @@
 ## Log Fold Change (LFC) Ordering Options
 
 ***
+💡 **Tip**: For more detailed information, please visit <a href="https://icb-dcm.github.io/cOmicsArt/interface-details/heatmap.html#conditional-options-for-top-k" target="_blank">here</a>.
+
 **1. Choose Type for LFC-Based Ordering:**
 
 - **Description:**

program/shinyApp/helpfiles/Heatmap_Options.md

@@ -1,8 +1,8 @@
-
----
-
 ## Row Selection Options
 
+***
+💡 **Tip**: For more detailed information, please visit <a href="https://icb-dcm.github.io/cOmicsArt/interface-details/heatmap.html#side-panel-" target="_blank">here</a>.
+
 **1. Row Selection Options:**
 
 - **Description**

program/shinyApp/helpfiles/Heatmap_RowAnnoBased.md

@@ -1,6 +1,7 @@
 ## Additional Row Selection Options
 
 ---
+💡 **Tip**: For more detailed information, please visit <a href="https://icb-dcm.github.io/cOmicsArt/interface-details/heatmap.html#conditional-options-for-select-based-on-annotation" target="_blank">here</a>.
 
 These options only make sense if you selected `rowAnno_based` in the `Row Selection`. 
 They serve to filter the row entities which to include in the heatmap.

program/shinyApp/helpfiles/PCA_Choices.md

@@ -1,6 +1,7 @@
 ## Principal Component Analysis (PCA) Options
 
 ***
+💡 **Tip**: For more detailed information, please visit <a href="https://icb-dcm.github.io/cOmicsArt/interface-details/pca.html#side-panel-" target="_blank">here</a>.
 
 A principal component analysis (PCA) is a linear dimensionality reduction technique to 
 visualize clusters within your data. For a small introduction on PCAs, please refer to 

program/shinyApp/helpfiles/PreProcessing_DESeqMain.md

@@ -1,5 +1,8 @@
 ## DESeq Factor Choices
 
+***
+💡 **Tip**: For more detailed information, please visit <a href="https://icb-dcm.github.io/cOmicsArt/interface-details/pre-processing.html" target="_blank">here</a>.
+
 ### Understanding the Design Matrix in DESeq2
 
 The design matrix in DESeq2 is a fundamental component used to specify the experimental design of your RNA-seq dataset. It helps in determining the relationship between the observed counts and the experimental conditions. Here's a detailed explanation:

program/shinyApp/helpfiles/PreProcessing_Procedures.md

@@ -1,4 +1,6 @@
 ## Data Preprocessing
+***
+💡 **Tip**: For more detailed information, please visit <a href="https://icb-dcm.github.io/cOmicsArt/interface-details/pre-processing.html" target="_blank">here</a>.
 
 **Step 1: General Data Cleaning**
 

program/shinyApp/helpfiles/SampleCorr_Choices.md

@@ -1,6 +1,7 @@
 ## Correlation method
 
 ***
+💡 **Tip**: For more detailed information, please visit <a href="https://icb-dcm.github.io/cOmicsArt/interface-details/sample-correlation.html" target="_blank">here</a>.
 
 Choose **one** of the following correlation methods. These correlation methods provide 
 insights into different aspects of relationships between variables. Understanding 

program/shinyApp/helpfiles/SampleCorr_Color.md

@@ -1,6 +1,7 @@
 ## Color Annotation
 
 ***
+💡 **Tip**: For more detailed information, please visit <a href="https://icb-dcm.github.io/cOmicsArt/interface-details/sample-correlation.html" target="_blank">here</a>.
 
 You can choose **Multiple** options. Each option is a column from the `sample 
 annotation table`. The clustered samples will be colored on the right side by your 

program/shinyApp/helpfiles/SampleCorr_Downloads.md

@@ -1,6 +1,7 @@
 ## Download Helper
 
 ***
+💡 **Tip**: For more detailed information, please visit <a href="https://icb-dcm.github.io/cOmicsArt/interface-details.html#features-across-tabs" target="_blank">here</a>.
 
 These buttons serve for various downloading purposes.
 

program/shinyApp/helpfiles/SigAna_Choices.md

@@ -1,5 +1,8 @@
 ## Significance Analysis Options
 
+***
+💡 **Tip**: For more detailed information, please visit <a href="https://icb-dcm.github.io/cOmicsArt/interface-details/significance-analysis.html#main-panel-" target="_blank">here</a>.
+
 **1. Choose Groups to Compare:**
 
 - **Description:**

program/shinyApp/helpfiles/SigAna_Intersections.md

@@ -1,6 +1,8 @@
 ## Highlight and Download intersections
 
 ***
+💡 **Tip**: For more detailed information, please visit <a href="https://icb-dcm.github.io/cOmicsArt/interface-details/significance-analysis.html#main-panel-" target="_blank">here</a>.
+
 To allow for a better overview of the intersections, the user can highlight the 
 intersections of interest. You can choose from all available intersections in the 
 `Intersections to highlight` menu. The intersection names shown in the Upset plot above, 

program/shinyApp/helpfiles/SigAna_Vis.md

@@ -1,6 +1,8 @@
 ## Visualizing Significance Analysis Results Options
 
 ***
+💡 **Tip**: For more detailed information, please visit <a href="https://icb-dcm.github.io/cOmicsArt/interface-details/significance-analysis.html#main-panel-" target="_blank">here</a>.
+
 **1. Select Comparisons to Visualize:**
 
 - **Description:**

program/shinyApp/helpfiles/SingleGene_Options.md

@@ -1,6 +1,8 @@
 ## Single Gene Visualization Options
 
 ---
+💡 **Tip**: For more detailed information, please visit <a href="https://icb-dcm.github.io/cOmicsArt/interface-details/single-gene-visualisations.html#side-panel-" target="_blank">here</a>.
+
 **1. Choose Data Type:**
 
 - **Description:**

program/shinyApp/helpfiles/SingleGene_Select.md

@@ -1,6 +1,8 @@
 ## Choosing groups for comparison
 
 ---
+💡 **Tip**: For more detailed information, please visit <a href="https://icb-dcm.github.io/cOmicsArt/interface-details/single-gene-visualisations.html#side-panel-" target="_blank">here</a>.
+
 This option lets you specify how to group the samples based on the annotation categories 
 provided in the sample annotation file. This only has an effect if you have chosen 
 `boxplots_withTesting` as the visualization style.

program/shinyApp/helpfiles/TakingNotesMD_help.md

@@ -1,5 +1,7 @@
 ## Personal Note Taking
 
+***
+💡 **Tip**: For more detailed information, please visit <a href="https://icb-dcm.github.io/cOmicsArt/interface-details.html#features-across-tabs" target="_blank">here</a>.
 
 This Section is here for your Notes. It can be as easy as just a keyword or as complex as an entire figure description or even an entire book (however I do think there are better tools for this).
 To enable possibilities to structure your text, involving headings, bullets points or colored chunks `markdown` syntax can be used.