Merge pull request #5217 from bernt-matthias/topic/data

rename Shared Data to Data

faqs/galaxy/datasets_import_from_data_library.md

@@ -9,7 +9,7 @@ contributors: [bebatut,shiltemann,nsoranzo,hexylena,wm75]
 
 As an alternative to uploading the data from a URL or your computer, the files may also have been made available from a *shared data library*:
 
-1. Go into **Shared data** (top panel) then **Data libraries**
+1. Go into **Data** (top panel) then **Data libraries**
 2. Navigate to {% if include.path %}: *{{ include.path }}* or {% endif %} the correct folder as indicated by your instructor.
    {% unless include.path %}- On most Galaxies tutorial data will be provided in a folder named **GTN - Material --> Topic Name -> Tutorial Name**. {% endunless %}
 3. Select the desired files

topics/epigenetics/tutorials/estrogen-receptor-binding-site-identification/tutorial.md

@@ -85,7 +85,7 @@ The first step of any ChIP-Seq data analysis is quality control of the raw seque
 >
 >    > <tip-title>Importing data from a data library</tip-title>
 >    >
->    > * Go into "Shared data" (top panel) then "Data libraries"
+>    > * Go into "Data" (top panel) then "Data libraries"
 >    > * Click on "Training data" and then "Analyses of ChIP-Seq data"
 >    > * Select interesting file
 >    > * Click on "Import selected datasets into history"

topics/microbiome/tutorials/general-tutorial/tutorial.md

@@ -111,7 +111,7 @@ has been sequenced using 454 GS FLX Titanium. For the tutorial, the original fas
 >
 >    > <tip-title>Importing data from a data library</tip-title>
 >    >
->    > * Go into "Shared data" (top panel) then "Data libraries"
+>    > * Go into "Data" (top panel) then "Data libraries"
 >    > * Click on "Training data" and then "Analyses of metagenomics data"
 >    > * Select interesting file
 >    > * Click on "Import selected datasets into history"

topics/transcriptomics/tutorials/mirna-target-finder/tutorial.md

@@ -749,7 +749,7 @@ Both AT4G14365 and AT1G26890 are not well characterized genes. In the case of AT
 As additional activity, you can try to repeat the workflow by using the sequences stored in the NCBI GEO database with the accession number `GSE119382`. In that case, we will compare gene expression patterns of mutants overexpressing the brassinosteroid receptor BRL3 under two experimental conditions: control and drought-stress. The required datasets are available in the data library:
 
 > <hands-on-title>Import data from the Data Libraries</hands-on-title>
-> 1. Go into __Shared data__ (top panel) and click on __Data Libraries__
+> 1. Go into __Data__ (top panel) and click on __Data Libraries__
 > 2. In the search box enter the following identifier: `4710649`
 > 3. Select the following files:
 > ```

topics/transcriptomics/tutorials/rna-seq-reads-to-counts/tutorial.md

@@ -508,7 +508,7 @@ We'll use a prepared workflow to run the first few of the QCs below. This will a
 
 ## Strandness
 
-As far as we know this data is unstranded, but as a sanity check you can check the strandness. You can use RSeQC Infer Experiment tool to "guess" the strandness, as explained in the [RNA-seq ref-based tutorial]({% link topics/transcriptomics/tutorials/ref-based/tutorial.md %}). This is done through comparing the "strandness of reads" with the "strandness of transcripts". For this tool, and many of the other RSeQC ({% cite wang2012rseqc %}) tools, a reference bed file of genes (`reference genes`) is required. RSeQC provides some reference BED files for model organisms. You can import the RSeQC mm10 RefSeq BED file from the link `https://sourceforge.net/projects/rseqc/files/BED/Mouse_Mus_musculus/mm10_RefSeq.bed.gz/download` (and rename to `reference genes`) or import a file from Shared data if provided. Alternatively, you can provide your own BED file of reference genes, for example from UCSC (see the [Peaks to Genes tutorial]({% link topics/introduction/tutorials/galaxy-intro-peaks2genes/tutorial.md %}). Or the **Convert GTF to BED12** tool can be used to convert a GTF into a BED file.
+As far as we know this data is unstranded, but as a sanity check you can check the strandness. You can use RSeQC Infer Experiment tool to "guess" the strandness, as explained in the [RNA-seq ref-based tutorial]({% link topics/transcriptomics/tutorials/ref-based/tutorial.md %}). This is done through comparing the "strandness of reads" with the "strandness of transcripts". For this tool, and many of the other RSeQC ({% cite wang2012rseqc %}) tools, a reference bed file of genes (`reference genes`) is required. RSeQC provides some reference BED files for model organisms. You can import the RSeQC mm10 RefSeq BED file from the link `https://sourceforge.net/projects/rseqc/files/BED/Mouse_Mus_musculus/mm10_RefSeq.bed.gz/download` (and rename to `reference genes`) or import a file from Data if provided. Alternatively, you can provide your own BED file of reference genes, for example from UCSC (see the [Peaks to Genes tutorial]({% link topics/introduction/tutorials/galaxy-intro-peaks2genes/tutorial.md %}). Or the **Convert GTF to BED12** tool can be used to convert a GTF into a BED file.
 
 > <hands-on-title>Check strandness with <b>Infer Experiment</b></hands-on-title>
 >