Galaxy beginner's tutorial

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Why Galaxy?

Because of the tools. Because of the data storage. Because of the computing power. Because of the reproducibility of your research. Because you don't want to install all the tools yourself that are available on our Galaxy.

In following tutorial, we will guide you in exploring Galaxy for your bioinformatics needs. If the Galaxy of BITS does not suffice your needs, please contact us via and we will get into touch whether we can meet them.

Before we begin

Before we begin, you have to log in on our Galaxy. If you don't have a login, please email to obtain one.


The analysis screen of Galaxy is divided in three sections

Tools at the left side, the middle pane in which the analysis results can be viewed, and the history on the right side showing the outputs of all previously run tools.

The black bar at the top provides an access point to more functionality, covered later on. In the top right corner you can see your storage usage as a bar.


Getting data in

Upload small (< 2GB) files from your computer

Do this via the tool 'Get data' and 'Upload file'.


Choose the file under 'File:' and click execute. Galaxy will try to automatically detect the type of file you have uploaded.


Handicon.png To keep better track of data, Galaxy wants to link all files to a certain genome. Set this at the bottom of the upload page if it applies to your dataset

The dataset appears in the history at the right pane (as output of the 'Upload data' tool).


Upload big files (> 2GB) using FTP

To send big files (>2GB) you must use FTP instead of the browser. This is a two-steps process. We use the ftp client Filezilla to do this. You can install Filezilla on your computer via your software manager (or 'sudo apt-get install filezilla' on Ubuntu) (see www. Connect with Filezilla to with your Galaxy email as username and your password.


At the left pane of Filezilla, contents on your local computer is visible. At the right, the directory at Galaxy is visible. Navigate to the file on your computer you want to upload, double-click on it and the upload should start.


When the upload is finished, go in Galaxy to 'Get data' -> 'Upload file' to get the data finally into Galaxy. The upload file(s) are shown in the section 'Files uploaded via FTP' of this tool. Select the ones you want to import and click on execute.


The dataset appears in the history at the right pane (as output of the 'Upload data' tool).


Get data in from a webservice

You can directly fetch data from a webservice as UCSC or Biomart. These are listed under 'Get data'. The site will appear in the middle pane of Galaxy: set the filters right and choose the 'Send file to Galaxy' option. The exact approach differs between tools. After this, the dataset should be visible in your history.


Datasets are collected in the history pane

Give your history a good name

It is good practice from the moment a dataset it present, to give your history an appropriate name. Just click on the title, type the new name and hit enter.


The different colors of datasets represent different states

Datasets in your history are in one of the five states:

  • Uploadinprogress.png Uploading is busy
  • Queuedexample.png A tool is queued: the resulting dataset does not exist yet
  • Runningtoolexample.png A tool is running: the resulting data is being generated
  • Toolingoodshape.png A tool has finished: the dataset is ready
  • Toolinerror.png A tool has encountered an error: the dataset is not to trust

Clicking on the title of a dataset expose some details of the dataset

Clicking on the name of the dataset in the history unfolds a preview and some tools to manipulate the data.


  • Showdataofdataset.png - displays the content in the middle pane
  • Editmetadata.png - edit the metadata (attributes) of the dataset, e.g. the type of data. Important!
  • Deletethedataset.png - deletes the dataset

  • Downloadthedataset.png - download the dataset to your computer
  • Moreinfoaboutthedataset.png - view more info, e.g. which parameters where used for generating the data
  • Runthisjobagain.png - run this job again, displaying the tool's settings in the middle pane. Important!

The following are only applicable for data which can be viewed in genomic context.

  • Viewintrackster.png - view in Trackster, the build-in genome browser
  • Tagthedataset.png - tag the dataset, so you can easily retrieve it by searching
  • Addcommenttothedataset.png - add comments to the dataset, especially useful if sharing this dataset with colleagues.

Explore the dataset yourself at

Datasets are assigned to a specific type

Click on Editmetadata.png to change these properties if required.

Within Galaxy, two major dataset properties must be set. Most of the time, the tool that generates the dataset get this straight. With uploaded data, you might have to do this yourself: the datatype and the genome build it is related too (see screenshot below). In addition, it is good practice to change the name of the dataset here to something descriptive.

Data types are used to filter the input for tools: e.g. mappers only accept 'fastqsanger' dataset types.


Note above: some types (e.g. bed, interval,...) require that also the names of the columns are set. You can preview these names in the little preview window, and set them correct by clicking on Editmetadata.png


Histories and their datasets are automatically saved

You can start a new history anytime. You will not stop jobs currently running in any history! Click Historyoptionsicons.png in the right upper corner, and select Create New (see screenshot at the right).


Choosing Saved Histories shows all your histories, with the number of datasets, colour-coded according to the state the datasets are in. Here you can switch between different histories to view their datasets.


Handicon.png You can even close the browser and come back later to check the status of your running jobs!

Security of your datasets and histories

All datasets generated by you belong to you by default. Galaxy allows setting permissions: on who can change access permissions, and on who can access datasets. Do this by clicking the Editmetadata.png of a dataset, and going to the bottom of the page.


The upper box allow you to set who can change access permissions. The lower box is the allow access box. You can select here only so-called roles: roles are collections of users or groups of users. Only admins of Galaxy currently can create groups and roles, but you always have your own 'private' role, to which all your datasets belong by default. More info on security on Galaxy's Official wiki

If sharing data with a user, permissions need to be adjusted, but luckily this can be done automatically.

Sharing histories

You can share histories with users. Click in the history menu on 'Publish or share'. You will see something similar as the screenshot below.


You can share in three ways:

  1. get a URL to your history, which you can email to other people (first button)
  2. get your history listed in the 'Published history' pages, listed under the top menu 'Shared Data'. (second button)
  3. share your history with (a) specific user(s) (third button)

Running tools on your datasets

Tools are organised in sections

You can browse the sections for the tool you need, or you can search the descriptions of the tools at the top.


Two main ways to run a tool

  • click on the name of the tool in the left pane: the tool loads with default parameter settings.
  • click on the 'Run this job again' button on a dataset Runthisjobagain.png: the tool which created that dataset loads again with the same settings.

Handicon.png If you don't see the dataset to use as input in the dropdown, make sure the datatype of the data set is correctly set.

The tool's parameters can be set in the middle pane. A tool is executed by pressing Executebutton.png. A new dataset (or sometimes more than one) is created in the history.


At the bottom you can find information about how to use the tools, and often also some examples.

Galaxy 'DNA' workshop exercises


Galaxy provides tools for all steps of 'next-gen' sequencing analysis. Analysis of sequencing data can be summarized as in the scheme depicted above. Below you can find tutorials to get you started with NGS analysis in Galaxy.

! Check your logins to access Galaxy for the Galaxy 'DNA' workshop

  1. Quality control of NGS data in Galaxy (Accompanying Galaxy history)
  2. Mapping of NGS data in Galaxy (Accompanying Galaxy history)
  3. Getting and manipulating genome tracks in Galaxy (Accompanying Galaxy history)

Handicon.png ! Looking for more tutorials? See this great tutorial on the Main Galaxy.

Handicon.png Make sure to follow some of these interesting lectures (~30 minutes each) about NGS and Genomics analyses by Rafael Irizarry