GTN Training: Galaxy 101 For Everyone 8.0
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Associated Tutorial
This workflows is part of the tutorial Galaxy Basics for everyone, available in the GTN
Features
- Includes Galaxy Workflow Tests
Thanks to...
Tutorial Author(s): Anne Fouilloux, Nadia Goué, Christopher Barnett, Michele Maroni, Olha Nahorna, Dave Clements, Saskia Hiltemann
Tutorial Contributor(s): Helena Rasche, Saskia Hiltemann, Matthias Bernt, Nicola Soranzo, Anne Fouilloux, Michele Maroni, Martin Čech, Jennifer Hillman-Jackson, Nadia Goué, Anthony Bretaudeau, Björn Grüning, Alex Ostrovsky, Mélanie Petera, Nate Coraor, David López, Bérénice Batut, Wendi Bacon
Funder(s): ELIXIR Europe
Inputs
| ID | Name | Description | Type |
|---|---|---|---|
| iris | #main/iris | n/a |
|
Steps
| ID | Name | Description |
|---|---|---|
| 1 | Convert CSV to tabular | csv_to_tabular |
| 2 | Datamash | toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.1.0 |
| 3 | Remove beginning | Remove beginning1 |
| 4 | Cut | Cut1 |
| 5 | Group | Grouping1 |
| 6 | Group | Grouping1 |
| 7 | Scatterplot with ggplot2 | toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.3.5+galaxy0 |
| 8 | Scatterplot with ggplot2 | toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.3.5+galaxy0 |
| 9 | Unique | toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/1.1.0 |
Outputs
| ID | Name | Description | Type |
|---|---|---|---|
| _anonymous_output_1 | #main/_anonymous_output_1 | n/a |
|
| _anonymous_output_2 | #main/_anonymous_output_2 | n/a |
|
| datamash_output | #main/datamash_output | n/a |
|
| group1 | #main/group1 | n/a |
|
| group2 | #main/group2 | n/a |
|
| unique_output | #main/unique_output | n/a |
|
Version History
master
Creators and Submitter
Views: 37 Downloads: 3 Runs: 0
Created: 2nd Jun 2025 at 10:57
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Related items
Teams: Galaxy Training Network
Organizations: Galaxy
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Galaxy is an open, web-based platform for accessible, reproducible, and transparent computational biological research.
- Accessible: Users can easily run tools without writing code or using the CLI; all via a user-friendly web interface.
- Reproducible: Galaxy captures all the metadata from an analysis, making it completely reproducible.
- Transparent: Users share and publish analyses via interactive pages that can enhance analyses with user annotations.
- Scalable: Galaxy can run ...
Teams: Galaxy Training Network
Web page: https://galaxyproject.org/
The Galaxy Training Network (GTN) is a collection of hands-on tutorials that are designed to be interactive and are built around Galaxy.
These tutorials can be used for learning and teaching how to use Galaxy for general data analysis, as well as a wide array of hands-on tutorials covering specific domains such as assembly, RNA-Seq analysis, deep learning, climate analysis, and more!
