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| # Workflow upload | ||
| # A workflow of your use-case | ||
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| Same as data libraries, you can import workflows, from shared data that has been pre-set in your Galaxy server for this training session. | ||
| The exercise of this week is difficult: | ||
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| To access these workflows : | ||
| You are going to prepare a complete workflow of your analysis. | ||
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| ---- | ||
|  | ||
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| 1. Click the menu `Données partagées` (`Shared data`) and select the submenu | ||
| `Workflows`. You should see two workflows : `paired-data-STAR-RNAseq` and `paired-data-HISAT2-RNAseq` | ||
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| 2. For each workflow, click on the arrow and select `Import`. | ||
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| Now, you'll be able to see these workflows in the `Workflow` menu. | ||
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| ---- | ||
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| # Running workflows | ||
| Depending on your model organisms, you may not have been able to perform all of the | ||
| analyses covered in this training. This is not a problem: you are expected to create a | ||
| workflow from what you have actually been able to do. | ||
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| You need to return to our first galaxy history `Inputs`, to do so : | ||
| In order to make a sustainable, reproducible and transparent workflow, you should meet the | ||
| following requirements: | ||
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| ---- | ||
|  | ||
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| 1. Click the menu `Utilisateur` and select the submenu | ||
| `Historiques sauvegardés`. | ||
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| 2. Click on `Inputs`. Its status is now **current history**. | ||
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| ---- | ||
| ## Workflow inputs | ||
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| ## Prepare inputs | ||
| Best inputs are | ||
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| These workflows use data collection as inputs, one per condition `treat` and `untreat`. Let's create our two data collections ! | ||
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| ---- | ||
|  | ||
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| 1. Click on the checked box.  | ||
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| 2. Select all treated datasets in pair ends : | ||
| - `GSM461180_1_treat_paired.fastq.gz` | ||
| - `GSM461181_1_treat_paired.fastq.gz` | ||
| - `GSM461180_2_treat_paired.fastq.gz` | ||
| - `GSM461181_2_treat_paired.fastq.gz` | ||
| - [x] Completely unprocessed data (i.e. fastq files) | ||
| - [x] Preferably accessible through a sustainable URL. If it is not possible, they should | ||
| be at least easily accessible (i.e. gathered in a single folder, whose location is | ||
| precisely described) | ||
| - [x] reference data (GTF, bed, etc...) should be precisely annotated, date, organisation, | ||
| version, etc... Importantly, a **direct** URL to the original reference should be included | ||
| - [x] :warning: Unless impossible to do, do not use processed data as inputs of your | ||
| workflow. If you think this is impossible to do, **let's discuss it** ! | ||
| - A lot of good workflows stand on a metadata table, which describes input data, their | ||
| names, labels if required, replicate status, etc. This metadata table may be considered | ||
| as a genuine dataset which can be used by the workflow to perform some operations. | ||
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| 3. Then click on the button `Pour toute la sélection...` and `Build List of Dataset Pairs`. | ||
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| 4. Enter a name for your dataset collection. `Name`: Treat data pairs. | ||
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| 5. `Create list` | ||
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| ---- | ||
|  | ||
| ## Computational steps | ||
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| Redo a data collections for untreated datasets. | ||
| - [x] Whenever a computational step applies to multiple sample, think "**Collections**" | ||
| - [x] A good clue that you should switch to collections is when your workflow contains | ||
| twice or more the same step with the same parameters (or almost the same) | ||
| - [x] Take the time, for each step, to carefully fill the tool form at the right hand-side | ||
| of the workflow editor. | ||
| - [x] There are several fields in this tool form that *must* be used to clarify the step: | ||
| The `Label` field at the top of the tool form, the `Step Annotation` field, and the | ||
| `Configure Output: xxx` fields and their sub-fields `Label`, `Rename dataset` and `Change | ||
| datatype` | ||
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| 1. Unchecked the previous datasets. | ||
| Experiment theses fields with your workflow ! | ||
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| 2. Select all untreated datasets in pair ends : | ||
| - `GSM461177_1_untreat_paired.fastq.gz` | ||
| - `GSM461178_1_untreat_paired.fastq.gz` | ||
| - `GSM461177_2_untreat_paired.fastq.gz` | ||
| - `GSM461178_2_untreat_paired.fastq.gz` | ||
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| 3. Then click on the button `Pour toute la sélection...` and `Build List of Dataset Pairs`. | ||
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| 4. Enter a name for your dataset collection. `Name`: Untreat data pairs. | ||
| - [x] Workflow **can use parameters** at their runtime. If you are interested by this functionality, | ||
| let's discuss it ! | ||
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| 5. `Create list` | ||
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| ---- | ||
| ## Workflow outputs | ||
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| You are now the happy owner of two dataset paired collections ! | ||
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| It's time to test the worflows ! | ||
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| ---- | ||
|  | ||
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| 1. Go to Menu `Workflow`. | ||
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| 2. For the workflow `imported: paired-data-HISAT2-RNAseq`, click on the arrow and then `Run`. | ||
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| 3. `History Options` | ||
| - `Send results to a new history`: Yes | ||
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| 4. `1: treated data pairs`: Treat data pairs | ||
| - [x] You can hide some output datasets for better readability of the workflow by | ||
| unchecking this outputs in the tool items of the workflow. | ||
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| :warning: By default all outputs are visible although unchecked. This is only when you | ||
| check a first output that unchecked outputs become hidden. | ||
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| :warning: Hidden does not mean deleted: all workflow outputs are still there and you can | ||
| reveal them in the Galaxy history. | ||
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| 5. `2:GTF`: Drosophila_melanogaster.BDGP6.95.gtf.gz | ||
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| 6. `3: un-treated data pairs`: Untreat data pairs | ||
| - [x] Whenever possible, rename your datasets in the workflow using the `Configure Output: xxx` | ||
| fields in the tool forms | ||
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| 7. `Run workflow` | ||
| ## Your objective: | ||
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| ---- | ||
| Is that you generate the complete analysis in a **single** workflow run, with the minimal | ||
| number of inputs. | ||
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|  | ||
| This way, you can even loose/trash your Galaxy history : | ||
| Just having the inputs plus the workflow should be enough to regenerate the analysis. | ||
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| Redo the same for the workflow `imported: paired-data-STAR-RNAseq`. | ||
| Consider that it is also a **huge** gain in term of data storage. |
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