Boxes are banned as initial content, they break json-ld and our abstr…

…acts

topics/admin/tutorials/object-store/tutorial.md

@@ -27,18 +27,12 @@ requirements:
      - ansible-galaxy
 ---
 
-> <warning-title>switching object store types will cause issues</warning-title>
-> Do not run this tutorial on your production instance! We will switch between object stores during this tutorial which has serious implications for production servers.
-{: .warning}
-
-# Expanding Storage
-
-
-
 You may find that your Galaxy files directory has run out of space, but you don't want to move all of the files from one filesystem to another. One solution to this problem is to use Galaxy's hierarchical object store to add an additional file space for Galaxy.
 
 Alternatively, you may wish to write new datasets to more than one filesystem. For this, you can use Galaxy's distributed object store.
 
+# Expanding Storage
+
 This tutorial assumes you have done the "Ansible for installing Galaxy" tutorial, it references the base configuration set up in that tutorial in numerous places.
 
 > <agenda-title></agenda-title>
@@ -48,6 +42,9 @@ This tutorial assumes you have done the "Ansible for installing Galaxy" tutorial
 >
 {: .agenda}
 
+> <warning-title>switching object store types will cause issues</warning-title>
+> Do not run this tutorial on your production instance! We will switch between object stores during this tutorial which has serious implications for production servers.
+{: .warning}
 
 # Hierarchical Object Store
 

topics/admin/tutorials/reports/tutorial.md

@@ -30,6 +30,8 @@ requirements:
       - ansible-galaxy
 ---
 
+The reports application gives some pre-configured analytics screens. These are very easy to setup and can help with debugging issues in Galaxy.
+
 > <warning-title>Currently Broken, Requires Separate Domain</warning-title>
 > Reports does not work, under a path prefix (the default setup that most
 > people will use.) It is completely broken and the developers have no plans to fix it in the near term.
@@ -41,8 +43,6 @@ requirements:
 > tutorial, please be aware of this.
 {: .warning}
 
-The reports application gives some pre-configured analytics screens. These are very easy to setup and can help with debugging issues in Galaxy.
-
 > <agenda-title></agenda-title>
 >
 > 1. TOC

topics/data-science/tutorials/python-iterables/tutorial.md

@@ -38,7 +38,7 @@ notebook:
   pyolite: true
 ---
 
-
+Doing calculations with hundreds of variables called `pressure_001`, `pressure_002`, etc. would be at least as slow as doing them by hand. Using a *list* to store many values together solves that problems. Lists are surrounded by square brackets: `[`, `]`, with values separated by commas:
 
 > <agenda-title></agenda-title>
 >
@@ -49,9 +49,6 @@ notebook:
 >
 {: .agenda}
 
-# Lists
-
-Doing calculations with a hundred variables called `pressure_001`, `pressure_002`, etc. would be at least as slow as doing them by hand. Using a *list* to store many values together solves that problems. Lists are surrounded by square brackets: `[`, `]`, with values separated by commas:
 
 ```python
 pressures = [0.273, 0.275, 0.277, 0.275, 0.276]

topics/dev/tutorials/tool-generators-advanced/tutorial.md

@@ -60,12 +60,12 @@ recordings:
 
 ---
 
-# Background and a user's guide to this training material
-
 Galaxy users who write and share scripts useful for scientific analyses are likely to be reading this material, perhaps after seeing the "Hello Galaxy"
 demonstration. It was written to help you find out about the capabilities and limits of the ToolFactory by experimenting with it yourself.
 It is hoped that this advanced tutorial will introduce some features that potentially make the ToolFactory useful in your work.
 
+# Background and a user's guide to this training material
+
 This training material is unlike most other GTN tutorials. There is no specific tool building curriculum on offer because it is hard to know how
 that might be orgranised. The introductory `Hello Galaxy` demonstrations and
 hands-on are the only formal attempt at explaining any tool's structure and construction.

topics/dev/tutorials/writing_tests/tutorial.md

@@ -33,15 +33,6 @@ requirements:
 subtopic: core
 ---
 
-> <agenda-title></agenda-title>
->
-> 1. TOC
-> {:toc}
->
-{: .agenda}
-
-# Testing in Galaxy
-
 The Galaxy code base contains thousands of tests that include tests of different types (unit vs. functional vs. end-to-end; client vs. backend, etc.) that are supported by a variety of testing frameworks and libraries. In this tutorial, we will offer a small, yet representative sample of the types of tests you might write, as well as the concepts and issues you may need to be familiar with when writing tests for Galaxy code, whether as part of a new feature you are implementing, or as a standalone contribution to Galaxy's testing code.
 
 A good way to start learning about Galaxy's testing infrastructure and how to use it is to read the documentation article on the different types of tests that are present in the code base as well as how to determine which type is most appropriate for a given scenario (see [Writing Tests for Galaxy](https://docs.galaxyproject.org/en/master/dev/writing_tests.html)).
@@ -56,6 +47,14 @@ Another useful resource is the [Debugging Galaxy]({% link topics/dev/tutorials/d
 
 Finally, nothing can substitute studying Galaxy's test code - we encourage you to always look for examples of similar tests and testing scenarios before you write your own.
 
+
+> <agenda-title></agenda-title>
+>
+> 1. TOC
+> {:toc}
+>
+{: .agenda}
+
 # Local development environment setup
 
 {% snippet topics/dev/faqs/contributing.md %}

topics/epigenetics/tutorials/methylation-seq/tutorial.md

@@ -21,6 +21,11 @@ contributors:
   - dpryan79
 ---
 
+We will use a small subset of the original data. If we would do the computation on the orginal data the computation time for a tutorial is too long. To show you all necessary steps for Methyl-Seq we decided to use a subset of the data set. In a second step we use precomputed data from the study to show you different levels of methylation. We will consider samples from normal breast cells (NB), fibroadenoma (noncancerous breast tumor, BT089), two invasive ductal carcinomas (BT126, BT198) and a breast adenocarcinoma cell line (MCF7).
+
+This tutorial is based off of {% cite Lin2015 %}. The data we use in this tutorial is available at [Zenodo](https://zenodo.org/record/557099).
+
+
 > <agenda-title></agenda-title>
 >
 > In this tutorial, we will deal with:
@@ -30,10 +35,6 @@ contributors:
 >
 {: .agenda}
 
-We will use a small subset of the original data. If we would do the computation on the orginal data the computation time for a tutorial is too long. To show you all necessary steps for Methyl-Seq we decided to use a subset of the data set. In a second step we use precomputed data from the study to show you different levels of methylation. We will consider samples from normal breast cells (NB), fibroadenoma (noncancerous breast tumor, BT089), two invasive ductal carcinomas (BT126, BT198) and a breast adenocarcinoma cell line (MCF7).
-
-This tutorial is based off of {% cite Lin2015 %}. The data we use in this tutorial is available at [Zenodo](https://zenodo.org/record/557099).
-
 
 # Data upload
 

topics/fair/tutorials/fair-ena/tutorial.md

@@ -38,16 +38,7 @@ contributions:
 subtopic: fair-data
 
 ---
-> <agenda-title></agenda-title>
->
-> In this tutorial we will deal with:
->
-> 1. TOC
-> {:toc}
->
-{: .agenda}
 
-# 01. Introduction
 DNA sequencing has become one of the key technologies in molecular biology, with applications in diagnostics, evolutionary biology, drug discovery, forensics and much more. Drop in sequencing costs and breakthroughs in sequencing technologies has seen increasing utilization of sequencing as a research tool, featuring in thousands of life-science publications every year. 
 
 Prior to publication many journals and funders require authors to submit their raw sequence data to one of the three INSDC member databases – **ENA, NCBI or DDBJ** – between which data is synchronised on a daily basis. INSDC is the core infrastructure for sharing nucleotide sequence data and metadata in the public domain. Data in INSDC member databases is available permanently, for free and with unrestricted access. For each submitted sequence a unique accession number is issued which can be reported in the publication. 
@@ -62,6 +53,16 @@ If you would like to use Galaxy tools for submission to ENA you may find [Submit
 > cURL is a command-line tool and library for transferring data over the internet. It allows you to send and receive data from various protocols like HTTP, FTP, and more. In simple terms, it's a tool that helps your computer talk to other computers on the internet and fetch or send information, like downloading files from a website or making API requests. 
 {: .tip}
 
+> <agenda-title></agenda-title>
+>
+> In this tutorial we will deal with:
+>
+> 1. TOC
+> {:toc}
+>
+{: .agenda}
+
+
 ## ENA Submission Routes
 
 There are three routes via which one can submit data to ENA. 

topics/galaxy-interface/tutorials/processing-many-samples-at-once/tutorial.md

@@ -18,6 +18,13 @@ contributors:
 subtopic: manage
 ---
 
+Here we will show Galaxy features designed to help with the analysis of large numbers of samples. When you have just a few samples - clicking through them is easy. But once you've got hundreds - it becomes very annoying. In Galaxy we have introduced **Dataset collections** that allow you to combine numerous datasets in a single entity that can be easily manipulated.
+
+In this tutorial we assume the following:
+
+- you already have basic understanding of how Galaxy works
+- you have an account in Galaxy
+
 > <agenda-title></agenda-title>
 >
 > In this tutorial, we will deal with:
@@ -27,17 +34,6 @@ subtopic: manage
 >
 {: .agenda}
 
-# Processing many samples at once
-
-Here we will show Galaxy features designed to help with the analysis of large numbers of samples. When you have just a few samples - clicking through them is easy. But once you've got hundreds - it becomes very annoying. In Galaxy we have introduced **Dataset collections** that allow you to combine numerous datasets in a single entity that can be easily manipulated.
-
-#### In this tutorial we assume the following:
-
-- you already have basic understanding of how Galaxy works
-- you have an account in Galaxy
-
-{% icon warning %} *At this time this tutorial is using Galaxy's test server at https://test.galaxyproject.org. Once the main site is updated this tutorial will be edited.*
-
 # Getting data
 [In this history](https://test.galaxyproject.org/u/anton/h/collections-1) are a few datasets we will be practicing with (as always with Galaxy tutorial you can upload your own data and play with it instead of the provided datasets):
 

topics/introduction/tutorials/vsi_qc/tutorial.md

@@ -20,6 +20,8 @@ draft: true
 
 ---
 
+In this tutorial we will look at assessing quality of data from two short read technologies: [Illumina](http://www.nature.com/doifinder/10.1038/nature07517) and [Element Biosciences](http://dx.doi.org/10.1038/s41587-023-01750-7). 
+
 > <agenda-title></agenda-title>
 >
 > In this tutorial, we will cover:
@@ -29,9 +31,6 @@ draft: true
 >
 {: .agenda}
 
-# Introduction
-
-In this tutorial we will look at assessing quality of data from two short read technologies: [Illumina](http://www.nature.com/doifinder/10.1038/nature07517) and [Element Biosciences](http://dx.doi.org/10.1038/s41587-023-01750-7). 
 
 ## FASTQ format
 

topics/microbiome/tutorials/dada-16S/tutorial.md

@@ -40,18 +40,18 @@ edam_ontology:
 
 ---
 
-> <comment-title>Sources</comment-title>
->
-> This tutorial is significantly based on [DADA2 Pipeline Tutorial](https://benjjneb.github.io/dada2/tutorial.html) and ["Introduction to dada2"](https://bioconductor.org/packages/devel/bioc/vignettes/dada2/inst/doc/dada2-intro.html)
->
-{: .comment}
-
 The investigation of environmental microbial communities and microbiomes has been revolutionized by the 
 development of high-throughput amplicon sequencing. In amplicon sequencing a particular genetic locus, 
 for example the 16S rRNA gene (or a part of it) in bacteria, is amplified from DNA extracted from the community of interest, 
 and then sequenced on a next-generation sequencing platform. This technique removes the need to culture 
 microbes in order to detect their presence, and cost-effectively provides a deep census of a microbial community.
 
+> <comment-title>Sources</comment-title>
+>
+> This tutorial is significantly based on [DADA2 Pipeline Tutorial](https://benjjneb.github.io/dada2/tutorial.html) and ["Introduction to dada2"](https://bioconductor.org/packages/devel/bioc/vignettes/dada2/inst/doc/dada2-intro.html)
+>
+{: .comment}
+
 {% include topics/microbiome/tutorials/mothur-miseq-sop/background_16S.md %}
 
 To process 16S amplicon sequencing data, several tools exist: **QIIME2** ({% cite Bolyen_2019 %}), **Mothur** ({% cite Schloss_2009 %}), **Lotus2** ({% cite _zkurt_2022 %}), and **DADA2** ({% cite Callahan_2016 %}). All these tools can be used in Galaxy. In this tutorial we will use **DADA2**.

topics/teaching/tutorials/hybrid-training/tutorial.md

@@ -23,16 +23,16 @@ contributions:
     - gallantries
 ---
 
-> <tip-title>Combine with Australia Biocommon paper</tip-title>
-> This is an excellent companion paper: {% cite Hall_2021 %}
-{: .tip}
-
 **hybrid training events**, i.e. pairing-up on-site helpers with remote instructors across multiple sites simultaneously:
 
 ![Hybrid training diagram, a single remote instructor broadcasts training to multiple sites](./images/hybrid_training.png)
 
 With this model, we aim to bring training events to the trainees while reducing the environmental impact of instructor travel.
 
+> <tip-title>Combine with Australia Biocommon paper</tip-title>
+> This is an excellent companion paper: {% cite Hall_2021 %}
+{: .tip}
+
 # What is an hybrid training event?
 
 *To illustrate a typical Gallantries event and the different roles (1 person can have several roles), we have decided to share a story with several fictional characters*