Merge pull request #1 from erasche/fotis-update

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bgruening · Dec 9, 2019 · b17475c · b17475c
2 parents 8b3fbe5 + 0d9f1a5
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diff --git a/snippets/launch_rstudio.md b/snippets/launch_rstudio.md
@@ -1,7 +1,21 @@
+> ### {% icon hands_on %} Hands-on: Launch RStudio
 >
->    > ### {% icon tip %} Tip: Launch RStudio in Galaxy
->    > 1. Open the Rstudio tool {% icon tool %} by clicking [here](https://usegalaxy.eu/?tool_id=interactive_tool_rstudio)
->    > 2. Click Execute
->    > <!-- TODO: update to tool panel search -->
->    {: .tip}
->
+>  Depending on which server you are using, you may be able to run RStudio directly in Galaxy. If that is not available, RStudio Cloud can be an alternative.
+>
+> > ### {% icon tip %} Tip: Launch RStudio in Galaxy
+> > Currently RStudio in Galaxy is only available on [UseGalaxy.eu](https://usegalaxy.eu)
+> >
+> > 1. Open the Rstudio tool {% icon tool %} by clicking [here](https://usegalaxy.eu/?tool_id=interactive_tool_rstudio)
+> > 2. Click Execute
+> > 3. The tool will start running and will stay running permanently
+> > 4. Click on the "User" menu at the top and go to "Active Interactive Tools" and locate the RStudio instance you started.
+> {: .tip}
+>
+> > ### {% icon tip %} Tip: Launch RStudio Cloud if not available on Galaxy
+> >
+> > If RStudio is not available on the Galaxy instance:
+> > 1. Register for [RStudio Cloud](https://client.login.rstudio.cloud/oauth/login?show_auth=0&show_login=1&show_setup=1), or login if you already have an account
+> > 2. Create a new project
+> {: .tip}
+>
+{: .hands_on}
diff --git a/snippets/launch_rstudio_cloud.md b/snippets/launch_rstudio_cloud.md
diff --git a/topics/galaxy-ui/tutorials/rstudio/tutorial.md b/topics/galaxy-ui/tutorials/rstudio/tutorial.md
@@ -3,7 +3,6 @@ layout: tutorial_hands_on
 
 title: RStudio in Galaxy
 zenodo_link: ""
-enable: false
 questions:
 - How can I manipulate data using R in Galaxy?
 objectives:
@@ -44,12 +43,7 @@ contributors:
 
 ## Opening up RStudio
 
-> ### {% icon hands_on %} Hands-on: Open RStudio
->
-> 1. Start RStudio in Galaxy
-> 
->    {% include snippets/launch_rstudio_cloud.md %}
-{: .hands_on}
+{% include snippets/launch_rstudio.md %}
 
 You should now be looking at a page with the RStudio interface:
 
@@ -210,7 +204,7 @@ You have hopefully noticed a pattern - an R function has three key properties:
 
 What if you wanted to round to one significant digit, `round()` can do this, but you may first need to read the help to find out how.
 
-To see the help you need enter a `?` in front of the function name. The **Help** tab (in the bottom-right panel) will show you information. 
+To see the help you need enter a `?` in front of the function name. The **Help** tab (in the bottom-right panel) will show you information.
 
 > ### {% icon hands_on %} Hands-on: Get help
 >
@@ -220,7 +214,7 @@ To see the help you need enter a `?` in front of the function name. The **Help**
 >    > ?round()
 >    ```
 >
-> 2. Check the **Help** tab 
+> 2. Check the **Help** tab
 >
 {: .hands_on}
 

diff --git a/...na-seq-counts-to-viz-in-r/featurePlot.png → ...na-seq-counts-to-viz-in-r/featurePlot.png b/...na-seq-counts-to-viz-in-r/featurePlot.png → ...na-seq-counts-to-viz-in-r/featurePlot.png
diff --git a/topics/introduction/metadata.yaml b/topics/introduction/metadata.yaml
@@ -10,3 +10,12 @@ requirements:
 maintainers:
   - jennaj
   - tnabtaf
+
+
+subtopics:
+  - id: core
+    title: "Core"
+    description: "These are the core, foundational topics for learning how to use Galaxy."
+  - id: r
+    title: "R"
+    description: "These lessons focus on coding in R, using Galaxy analysis outputs as their basis."
diff --git a/topics/introduction/slides/introduction.html b/topics/introduction/slides/introduction.html
@@ -4,6 +4,7 @@
 
 title: "Introduction to Galaxy"
 type: "introduction"
+subtopic: core
 contributors:
   - bagnacan
   - bebatut

diff --git a/topics/introduction/tutorials/galaxy-intro-101-everyone/tutorial.md b/topics/introduction/tutorials/galaxy-intro-101-everyone/tutorial.md
@@ -21,6 +21,7 @@ key_points:
   - "Workflows enable you to repeat your analysis on different data"
   - "Galaxy can connect to external sources for data import and visualization purposes"
   - "Galaxy provides ways to share your results and methods with others"
+subtopic: core
 contributors:
   - annefou
   - nagoue

diff --git a/topics/introduction/tutorials/galaxy-intro-101/tutorial.md b/topics/introduction/tutorials/galaxy-intro-101/tutorial.md
@@ -20,6 +20,7 @@ key_points:
   - "Workflows enable you to repeat your analysis on different data"
   - "Galaxy can connect to external sources for data import and visualization purposes"
   - "Galaxy provides ways to share your results and methods with others"
+subtopic: core
 contributors:
   - shiltemann
   - nsoranzo

diff --git a/topics/introduction/tutorials/galaxy-intro-ngs-data-managment/tutorial.md b/topics/introduction/tutorials/galaxy-intro-ngs-data-managment/tutorial.md
@@ -15,6 +15,7 @@ key_points:
   - "FastqQC is a tool allowing to check the quality of FASTQ datasets."
   - "The most common tools for mapping are Bowtie, BWA, BWA-MEM. You can use in-built genome to map against or upload one if it is missing."
   - "The standard format for storing aligned reads is SAM/BAM. The major toolsets to process these datasets are DeepTools, SAMtools, BAMtools and Picard."
+subtopic: core
 contributors:
   - nekrut
 ---
@@ -184,7 +185,7 @@ The base qualities allow us to judge how trustworthy each base in a sequencing r
 > Due to the imperfect nature of the sequencing process and limitations of the optical instruments, base calling will always have inherent uncertainty. This is the reason why FASTQ files store the DNA sequence of each read together with a position-specific quality score that represents the error probability, i.e., how likely it is that an individual base call may be incorrect. The score is called [Phred score](http://www.phrap.com/phred/), $$Q$$, which is proportional to the probability $$p$$ that a base call is incorrect, where $$Q = −10lg(p)$$. For example, a Phred score of 10 corresponds to one error in every ten base calls ($$Q = −10lg(0.1)$$), or 90% accuracy; a Phred score of 20 corresponds to one error in every 100 base calls, or 99% accuracy. A higher Phred score thus reflects higher confidence in the reported base.
 >
 > To assign each base a unique score identifier (instead of numbers of varying character length), Phred scores are typically represented as ASCII characters. At http://ascii-code.com/ you can see which characters are assigned to what number.
-> 
+>
 > For raw reads, the range of scores will depend on the sequencing technology and the base caller used (Illumina, for example, used a tool called Bustard, or, more recently, RTA). Unfortunately, Illumina has been anything but consistent in how they calculated and ASCII-encoded the Phred score (see below)! In addition, Illumina now allows Phred scores for base calls with as high as 45, while 41 used to be the maximum score until the HiSeq X. This may cause issues with downstream sapplications that expect an upper limit of 41.
 {: .comment}
 
@@ -205,7 +206,7 @@ One of the first steps in the analysis of NGS data is seeing how good the data a
 
 |                                        |                                    |
 |:---------------------------------------|:-----------------------------------|
-| ![Good quality in FastQC](../../images/good_fq.png)    | ![Bad quality in FastQC](../../images/bad_fq.png) |    
+| ![Good quality in FastQC](../../images/good_fq.png)    | ![Bad quality in FastQC](../../images/bad_fq.png) |
 |<small>**A.** Excellent quality</small> | <small>**B.** Hmmm...OK</small>    |
 
 Here you can see FastQC base quality reports (the tools gives you many other types of data) for two datasets: **A** and **B**. The **A** dataset has long reads (250 bp) and very good quality profile with no qualities dropping below [phred score](http://www.phrap.com/phred/) of 30. The **B** dataset is significantly worse with ends of the reads dipping below phred score of 20. The **B** reads may need to be trimmed for further processing.

diff --git a/topics/introduction/tutorials/galaxy-intro-peaks2genes/tutorial.md b/topics/introduction/tutorials/galaxy-intro-peaks2genes/tutorial.md
@@ -21,6 +21,7 @@ key_points:
   - "Workflows enable you to repeat your analysis on different data"
   - "Galaxy can connect to external sources for data import and visualization purposes"
   - "Galaxy provides ways to share your results and methods with others"
+subtopic: core
 contributors:
   - pajanne
   - blankclemens

diff --git a/topics/introduction/tutorials/galaxy-intro-short/tutorial.md b/topics/introduction/tutorials/galaxy-intro-short/tutorial.md
@@ -21,6 +21,7 @@ key_points:
   - "View the output files by clicking on the eye icon."
   - "View all your histories and move files between them. Switch to a different history."
   - "Log out of your Galaxy server. When you log back in (to the same server), your histories will all be there."
+subtopic: core
 contributors:
   - annasyme
 

diff --git a/topics/introduction/tutorials/galaxy-intro-strands/tutorial.md b/topics/introduction/tutorials/galaxy-intro-strands/tutorial.md
@@ -16,6 +16,7 @@ key_points:
   - "Workflows enable you to repeat your analysis on different data"
   - "Galaxy can connect to external sources for data import and visualization purposes"
   - "Galaxy provides ways to share your results and methods with others"
+subtopic: core
 contributors:
   - tnabtaf
 ---

diff --git a/topics/introduction/tutorials/options-for-using-galaxy/slides.html b/topics/introduction/tutorials/options-for-using-galaxy/slides.html
@@ -9,6 +9,7 @@
 objectives:
 time_estimation:
 key_points:
+subtopic: core
 contributors:
   - tnabtaf
   - abretaud

diff --git a/topics/introduction/tutorials/r-advanced/tutorial.md b/topics/introduction/tutorials/r-advanced/tutorial.md
@@ -1,17 +1,16 @@
 ---
 layout: tutorial_hands_on
 
-title: R advanced in Galaxy
+title: Advanced R in Galaxy
+level: Intermediate
 zenodo_link: ""
-enable: false
 requirements:
   -
     type: "internal"
     topic_name: galaxy-ui
     tutorials:
         - rstudio
-
- -
+  -
     type: "internal"
     topic_name: introduction
     tutorials:
@@ -37,6 +36,7 @@ key_points:
 - Just like Galaxy, base R's capabilities can be further enhanced by software packages developed by the user community.
 - Use the `dplyr` package to manipulate data frames.
 - Pipes can be used to combine simple operations into complex procedures.
+subtopic: r
 contributors:
   - bebatut
   - fpsom
@@ -50,8 +50,9 @@ With HTS-Seq data analysis, we generated tables containing list of DE genes, the
 
 Sometimes we want to have some customizations on visualization, some complex table manipulations or some statistical analysis. If we can not find a Galaxy tools for that or the right parameters, we may need to use programming languages as R or Python.
 
+<!-- Keeping this here because people may be familiar enough with R, that they go directly to this tutorial, and it is still useful information. -->
+
 {% include topics/introduction/tutorials/r-basics/r_introduction.md %}
-{% include topics/introduction/tutorials/r-basics/r_advantages.md %}
 {% include topics/introduction/tutorials/r-basics/disclaimer.md %}
 
 In this tutorial, we will take the list of DE genes extracted from DESEq2's output that we generated in the ["Reference-based RNA-Seq data analysis" tutorial]({{ site.baseurl }}{% link topics/transcriptomics/tutorials/ref-based/tutorial.md %}), manipulate it and create some visualizations.

diff --git a/topics/introduction/tutorials/r-basics/start_rstudio.md b/topics/introduction/tutorials/r-basics/start_rstudio.md
diff --git a/topics/introduction/tutorials/r-basics/tutorial.md b/topics/introduction/tutorials/r-basics/tutorial.md
@@ -2,8 +2,8 @@
 layout: tutorial_hands_on
 
 title: R basics in Galaxy
+level: Introductory
 zenodo_link: ""
-enable: false
 requirements:
   -
     type: "internal"
@@ -26,6 +26,7 @@ objectives:
 time_estimation: 3H
 key_points:
 - It is important to understand how data are organised by R in a given object type (e.g. numeric, character, logical, etc.) and how the mode of that type determines how R will operate on that data.
+subtopic: r
 contributors:
   - bebatut
   - fpsom
@@ -50,7 +51,9 @@ contributors:
 >
 {: .agenda}
 
-{% include topics/introduction/tutorials/r-basics/start_rstudio.md %}
+Before diving in the tutorial, we need to open RStudio. If you do not know how or never interacted with RStudio, please follow the [dedicated tutorial]({{ site.baseurl }}{% link topics/galaxy-ui/tutorials/rstudio/tutorial.md %}).
+
+{% include snippets/launch_rstudio.md %}
 
 # Creating objects in R
 

diff --git a/topics/transcriptomics/tutorials/rna-seq-counts-to-viz-in-r/tutorial.md b/topics/transcriptomics/tutorials/rna-seq-counts-to-viz-in-r/tutorial.md
@@ -3,7 +3,6 @@ layout: tutorial_hands_on
 
 title: RNA Seq Counts to Viz in R
 zenodo_link: "https://zenodo.org/record/3477564/"
-enable: false
 requirements:
   -
     type: "internal"
@@ -45,9 +44,9 @@ With RNA-Seq data analysis, we generated tables containing list of DE genes, the
 
 Sometimes we want to have some customizations on visualization, some complex table manipulations or some statistical analysis. If we can not find a Galaxy tools for that or the right parameters, we may need to use programming languages as R or Python.
 
-{% include topics/introduction/tutorials/r-basics/r_introduction.md %}
-{% include topics/introduction/tutorials/r-basics/r_advantages.md %}
-{% include topics/introduction/tutorials/r-basics/disclaimer.md %}
+> ### {% icon tip %} Prerequisites
+> It is expected that you are already somewhat familiar with the R basics (how to create variables, create and access lists, etc.) If you are not yet comfortable with those topics, we recommend that you complete the requirements listed at the start of this tutorial first, before proceeding.
+{: .tip}
 
 In this tutorial, we will take the list of DE genes extracted from DESEq2's output that we generated in the ["Reference-based RNA-Seq data analysis" tutorial]({{ site.baseurl }}{% link topics/transcriptomics/tutorials/ref-based/tutorial.md %}), manipulate it and create some visualizations.
 
@@ -60,7 +59,7 @@ In this tutorial, we will take the list of DE genes extracted from DESEq2's outp
 >
 {: .agenda}
 
-{% include topics/introduction/tutorials/r-basics/start_rstudio.md %}
+{% include snippets/launch_rstudio.md %}
 
 # Visualization