Download Tutorial - Chemistry

An Introduction to Designing,
Executing and Sharing Workflows
with Taverna and myExperiment
Katy Wolstencroft
University of Manchester
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This tutorial will give you a basic introduction to
designing, and reusing workflows in Taverna and some
of its main features.
Workflows in this practical use small data-sets and are
designed to run in a few minutes. In the real world, you
would be using larger data sets and workflows would
typically run for longer
Exercise 1: Exploring the Workbench
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Taverna can be downloaded from
http://www.taverna.org.uk/
Go to the page and find the latest (2.4)
Follow the instructions on the website to install Taverna
for your operating system (this is a simple one-click
install for windows and Mac. For Linux, you may also
need the GraphViz program. Follow the link on the
Taverna download page if so)
The following page shows a screenshot of Taverna and
the different panels that make up the workbench
Taverna Workbench
Services Panel
Workflow
Explorer
Workflow
Diagram
1. Workflow Diagram
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The workflow diagram is the visual representation of the
workflow, it:
Shows inputs, outputs, services and data flows
Allows editing of the workflow by dragging and dropping
and connecting services together
Enables saving of workflow diagrams for publishing and
sharing
1. Workflow Explorer
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The Workflow Explorer shows the detailed view of your
workflow. It shows default values and descriptions for
service inputs and outputs and it shows where remote
services are located. It also shows configuration details,
such as iteration and looping
Workflow validation details can also be found here.
Before a workflow is run, Taverna checks to see if it is
connected correctly and if its services are available.
1. Available Services Panel
Lists services available by default in Taverna
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Local java services
WSDL Web Service – secure and public
RESTful Services
R Processor services (for statistical analyses)
Beanshell scripts
Xpath scripts
Spreadsheet import service
The services panel also allows you to add new services
or workflows from the web or from file systems – there
are loads more available!
1. Taverna exercises – Enrichment
Analysis
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Today, we will use Taverna to perform enrichment
analyses on a list of genes.
Many experiments result in a list of genes (e.g.
microarray analysis, Chip-Seq, SNP identification etc).
In this case, the genes are those associated with ChipSeq peaks
We will enrich our dataset by discovering:
Which pathways our genes are involved in
The functions of the genes
The cellular locations of the gene products
Literature evidence for the phenotype/trait of interest
Exercise 2: Building a Simple Workflow
As a simple start, we will find and invoke a single web service
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Go to the Services Panel in Taverna and type ‘pathway’
into the search box at the top
You will see several services in the search results
Select ‘get_pathways_by_genes’. This service returns all
pathways from KEGG
Drag this service
across to the workflow
explorer panel
2: Building a Simple Workflow
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In a blank space in the workflow
diagram panel, right-click and select
“Workflow Input Port”
Type in a name for this input (e.g. ID)
and click “ok”
Do the same to create a new
workflow output. Call this output
“pathways”
2: Building a Simple Workflow
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You now have 3 boxes in the diagram and we need to
connect them up
Click on the input box and drag towards
“get_pathways_by_genes” and let go. An arrow will
connect the two boxes
2: Building a Simple Workflow
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Click on the output box, drag
towards “get_pathways_bygenes”, and let go.
A pop-up will ask you to select
from ‘attachmentList’ and
‘return’. Select ‘return’
An arrow will connect the two
boxes
You have now built your first
workflow!
It should look something like this
2: Building a Simple Workflow
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Run the workflow by selecting “file -> run workflow”, or by
clicking on the play button at the top of the workbench
2: Building a Simple Workflow
An input window will appear. As you can see, we have not yet
added a description of the workflow or of the input
Click on ‘Set Value’ in the input window and add a KEGG Gene identifier
(e.g. mmu:13163) where it says “some input data goes here”
2: Building a Simple Workflow
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Click “run workflow”. You will automatically be switched
to the ‘Results’ window. Taverna will run the KEGG
Web Service in Japan to return pathways that gene is
involved in.
In the bottom left of the results window, click on the
results. You will see some pathway identifiers. These are
good for computers, but not for humans. We need
pathway descriptions to properly examine the results
Switch back to the ‘Design’ window using the tab at the
top of the workbench
2: Building a Simple Workflow
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In the service panel, search for another KEGG service,
called ‘btit’.
Drag and drop it into the same workflow
We can now connect the two services together
At the top of the workflow diagram panel, change the view to
show all ports by clicking on the icon shown below
Show all ports icon
2: Building a Simple Workflow
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Connect the
get_pathways_by_gene
‘return’ output to the input
(string) of btit
Create a new output called
‘pathway_description’ and
connect it the btit ‘return
output by dragging an arrow
between them
Re-run the workflow and look
at the pathway descriptions
The workflow will iterate over
each pathway ID to find each
description
2: Building a Simple Workflow
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A list of pathways and their descriptions is useful, but it
would be easier to visualise diagrams of the whole
pathways
Additionally, we need to find ALL the pathways for ALL the
genes in our lists in order to indentify which pathways are
over-represented in our data set
For both these tasks we will find and use workflows from
myExperiment
Exercise 3: Re-using workflows from
myExperiment
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Go to http://www.myexperiment.org and click on ‘find
workflows’
You will see a list of the most viewed and downloaded
workflow – see what the most popular workflow does by
reading the description
Change the rank to ‘Latest’ and see what has been
uploaded in the last few weeks
3: Re-using workflows from myExperiment
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Find the workflow called “geneID to KEGG Pathways” and
look at the workflow entry page (note: if your search returns
too many results, you can refine it by adding “Wolstencroft”
Download the workflow by clicking on the link: “Download
Workflow File/Package (T2FLOW)”
Open the workflow in Taverna by going to ‘File ->Open
Workflow’
Run the workflow using the example values supplied by the
workflow creator (Hint: when you run the workflow the
examples values will be added by default in the input
window)
Look at the workflow output – now you will see pathway
diagrams
Exercise 4: Combining workflows from
myExperiment
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To analyse all the genes from our study, we need to
extract the gene list from previous analysis results
To make it easier to work through the example, we have
provided a Chip-Seq gene list on myExperiment:
http://www.myexperiment.org/files/661.html
Save this file to your local machine
Open the file in Excel
Save the file with a .csv extension
As you can see, the list of genes is in column D
Taverna can process and extract this column
automatically
4: Combining workflows from myExperiment
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In myExperiment, find and download the workflow called
“Import and convert gene list”
This workflow will extract the list of genes in column D
using Taverna’s built-in spreadsheet import tool (which
can be found in the services panel, for future reference)
The next step in the workflow converts the RefSeq IDs
into unigene IDs (required for the pathways workflow –
converting between different types of identifiers is a
common problem in bioinformatics!)
Run the workflow. This time, in the input window, select
“set file location” and set the location to the saved .csv
gene list.
Look at the workflow results
4: Combining workflows from myExperiment
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We will now combine the two
workflows
While you are still in the
“import and convert” workflow,
go to the top of the workbench
and select “ insert -> Nested
workflow”
In the pop-up window, select
“import from file” and find the
pathways
workflow
you
downloaded earlier.
Click on “import workflow” and
the pathways workflow will
appear in the main workflow
diagram.
4: Combining workflows from myExperiment
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Connect the workflows up by linking the output of the
‘Merge_Gene_List’ with the nested workflow input
4: Combining workflows from myExperiment
Create new output ports for the Nested workflow and
connect the Nested workflow outputs to the new outputs
NOTE: you don’t need to connect them all, just pathway
descriptions, pathway images and gene descriptions
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Save the workflow
Run the workflow
4: Combining workflows from myExperiment
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The workflow may take a few minutes to run. Spend the
time looking at myExperiment to find other pathway-related
workflows
What other pathway workflows are there?
Do they all use KEGG?
What other resources could you use instead?
Exercise 5: GO Associations
There are many different tools we could use to find Gene
Ontology associations for your gene list
For example, we could simply modify the BioMart/Ensembl
service in the ‘Import and convert gene list’ workflow we
have already used
Reload the ‘Import and Convert gene list’ workflow
Right-click on the ‘mmusculus_gene_ensembl’ service
and select ‘Copy’
Paste an extra copy of this service into the same workflow
diagram
5: GO Associations
This is a BioMart service. It allows you to retrieve omics
data from ENSEMBL and other genomics resources. If you
are familiar with BioMart, you will see the interface in
Taverna is very similar to the web interface
We will modify the BioMart query to find all GO
associations for each gene associated with a Chip-Seq
peak
Right-click on the new copy of the service and select
‘Configure BioMart Query’
5: GO Associations
The inputs (or filters) already accept RefSeq Ids from our
input file, but we need to modify the outputs (or attributes)
Select ‘Attributes’ and expand the ‘External’ section.
Unselect ‘UniGeneID’ and select ‘RefSeq mRNA’
Additionally, select ‘Go Term Accession’, ‘GO Name’
and ‘Go Domain’
At the top of the page, change the output format from
multiple to single (TSV format)
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(See screenshot on the next slide for an example)
5: GO Associations
5: GO Associations
Click ‘apply’ to save your changes, and ‘close’, to go
back to Taverna
At the top of the workflow diagram, change the workflow
view to show all ports by clicking on the table icon
5: GO Associations
Connect your new service
to the workflow by linking
the ‘D’ output port of the
spreadsheet service to
the input of your new
service
Make a new output port
called ‘GO_Report’ and
connect it to your new
service
5: GO Associations
Save the workflow by going to ‘File -> Save Workflow’
Run the workflow
Download and view the GO report
Exercise 6: Adding New Services to Taverna
In Taverna, new tools can be ‘added’ very easily because
we are often actually calling external tools
 Go to http://www.biocatalogue.org and look around.
Biocatalogue is a registry of available Web Services for the
Life Sciences. You can use any of these tools in Taverna
 Search for the ‘ontology lookup service’
 Look at the entry for that service
 find and copy the WSDL location URL
HINT: it will be a URL ending in .wsdl (http://....wsdl)
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6. Adding New Services
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Go to the services panel in
Taverna and click “import
new services”. For each
type of service, you are
given the option to add a
new service
Select ‘WSDL service…’
A window will pop-up
asking for a URL
6. Adding New Services
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Enter the Ontology Lookup
service URL you just
copied
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Scroll down to the bottom
of the Services list in
Taverna and you will see
the new service you added
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It is now ready to be used
in your workflows
6: Adding New Services to Taverna
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Now we have Gene Ontology descriptions for our genes,
we might want to find out what other ontology descriptions
we can find
From the service set you have just imported, add the
service ‘getontologyname’ to a new workflow
This service does not require any inputs, so just create an
output port called ‘ontologyNames’ and connect it to the
service
Run the workflow
You will see a list of all ontologies you can search using
these services
Sometimes, documentation about services is embedded in
the service set like this
Exercise 7: Text Mining
So far we have looked at enriching the genomic
information, but we could also use workflows for running
data analyses (e.g. aligning mouse genes with human
homologues) or performing literature searches
Think about the ways you could extend this analysis with
literature searches (e.g. Correlations between pathways,
genes, GO terms, phenotypes etc)
Search myExperiment for workflows involving text mining,
using the search terms “text mining” and “Pubmed”
7: Text Mining
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Find and open the workflow “Phenotype to pubmed”
One of the services is no longer available in the nested
workflow (the faded-out service). Taverna checks the
availability of each service when you load the workflow and
when you run it
In this case, the workflow will still run without the final
nested workflow (clean text)
Delete the ‘clean text’ nested workflow (by selecting it and
right-clicking), and reconnect the workflow output
Run the workflow with the search term ‘erythropoiesis’
(or a phenotype term to describe the disease you are
studying)
8: Sharing Workflows
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If you want to save and share any workflows on
myExperiment, you can create an account and upload
them
If you wish to share them with each other, we can set up a
workshop group with restricted membership
8: Outcomes
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These exercises have given you a brief introduction to
Taverna, but we have just scratched the surface.
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The examples are taken from a real investigation, but the
data has been reduced to a level that will run in a few
minutes.
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If you would like to know more about using particular types
of services, for example REST, or R, or the External tools
plugin, we have other tutorial material. We also have
material to explain the advanced engine features, such as
iteration, looping, parallel invocation and retries.