add tip for collection upload

topics/transcriptomics/tutorials/minerva-pathways/tutorial.md

@@ -242,6 +242,19 @@ MultiQC report. Looking at the report we see generally reasonable quality data.
 >     - `Add Definition` → `List Identifier(s)` → Select Column `B`
 >     - `Add Definition` → `URL` → Column `A`
 >
+>     > <tip-title>Trouble entering?</tip-title>
+>     > 1. Press the {% icon tool %} button by **Rules**
+>     > 1. Paste the following JSON into the dialog:
+>     >    ```json
+>     >    {"rules":[],"mapping":[{"type":"collection_name","columns":[2]},{"type":"list_identifiers","columns":[1],"editing":false},{"type":"url","columns":[0]}],"genome":"hg19"}
+>     >    ```
+>     > 1. Click Apply
+>     {: .tip}
+>
+> 1. At the bottom of the dialog set `Genome` to `hg19` (it is probably something like "Human Feb 2009 (GRCh37/hg19) (hg19)" but we are focused on that last parenthetical portion).
+>
+> 1. Click **Upload**
+>
 {: .hands_on}
 
 </div>
@@ -250,17 +263,6 @@ Now we're ready to analyse the counts files. Here we'll take the feature counts
 
 With this result in hand we're ready to do two further steps: preparing the dataset for goseq, and for analysis in MINERVA. Goseq is a tool for gene ontology enrichment analysis, and MINERVA is a tool for visualising pathway analysis.
 
-The MINERVA dataset must be correctly formatted as a tabular dataset (`\t` separated values) like the following:
-
-```
-SYMBOL  logFC              P.Value               adj.P.Val
-TRIM25  2.07376444684004   1.2610025125617e-18   3.57368112059986e-15
-ACSL1   2.90647033200259   2.71976234791064e-16  3.85390324698937e-13
-NBEAL2  2.45952426389725   2.71787290816654e-14  2.56748394058132e-11
-MIR150  -2.55304226607428  9.55912390273625e-14  6.74866152827879e-11
-SLC2A3  2.95861349227708   1.19066011437523e-13  6.74866152827879e-11
-```
-
 <figure>
 {% assign wf_counts = site | get_workflow:page, "Galaxy-Workflow-mRNA-Seq_BY-COVID_Pipeline__Analysis.ga" %}
 <pre class="mermaid">
@@ -281,6 +283,17 @@ You should have a few outputs, namely the `goseq` outputs, and a table ready for
 
 ## MINERVA
 
+The dataset prepared for MINERVA must be correctly formatted as a tabular dataset (`\t` separated values) like the following, with the dbkey set to `hg19` or `hg38`. If you've run the above workflow, this should be the case.
+
+```
+SYMBOL  logFC              P.Value               adj.P.Val
+TRIM25  2.07376444684004   1.2610025125617e-18   3.57368112059986e-15
+ACSL1   2.90647033200259   2.71976234791064e-16  3.85390324698937e-13
+NBEAL2  2.45952426389725   2.71787290816654e-14  2.56748394058132e-11
+MIR150  -2.55304226607428  9.55912390273625e-14  6.74866152827879e-11
+SLC2A3  2.95861349227708   1.19066011437523e-13  6.74866152827879e-11
+```
+
 > <hands-on-title>Visualise in MINERVA</hands-on-title>
 >
 > 1. **Click** to expand the final "MINERVA-Ready Table"