Download Pathway Analysis using Partek Genomics Suite® 6.6 and Partek

Pathway Analysis using Partek Genomics Suite® 6.6 and
Partek Pathway™
Overview
Partek® Pathway™ provides a visualization tool for pathway enrichment
spreadsheets, utilizing KEGG and/or Reactome databases for human, rat and
mouse.
The screenshots shown below may vary across platforms and across different
versions of Partek.
Description of the Data Set
This guide uses the Affymetrix Gene ST dataset from the “Analyzing microRNA
Data and Integrating microRNA with Gene Expression Data in Partek® Genomics
Suite™ 6.6” tutorial.
Data and associated files for this tutorial can be downloaded by going to Help >
On-line Tutorials from the Partek main menu. The data can also be downloaded
directly from:
http://www.partek.com/Tutorials/microarray/microRNA/miRNA_tutorial_data.zip
Importing files
To proceed with the tutorial data, open the Partek pre-imported tutorial data that is
already in a Partek project format (.ppj): miRNAmRNA integration. This .ppj file
contains the Partek format file Affy_miR_BrainHeart_intensities.fmt with all the
microRNA data, and the Partek format file
Affy_HuGeneST_BrainHeart_GeneIntensities.fmt
with all the mRNA data. For the convenience of this tutorial, an ANOVA was
performed in the mRNA data and is opened as a child spreadsheet under the
Affy_HuGeneST_BrainHeart_GeneIntensities.fmt spreadsheet.
Select File > Open Project to invoke the project browser and open the
miRNAmRNA integration project - 3 spreadsheets will now be available:
1.
2.
3.
Affy_miR_BrainHeart_intensities
Affy_HuGeneST_BrainHeart_GeneIntensities
ANOVAResults gene (this is a child spreadsheet of the HuGeneST
Sheet)
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Streamlined ANOVA
The ANOVA spreadsheet contained within this dataset has 28869 rows; before
performing pathway analysis this list will be filtered to give a list of significant
regulated genes between the two organs.
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Invoke the Gene Expression workflow
Highlight the ANOVA spreadsheet
Select Create Gene List from the Analysis section – as you have already
highlighted an ANOVA spreadsheet you now have the ANOVA
Streamlined tab selected automatically
Configure as shown (Figure 1) and click Create – a new list of 420 genes
will be created
Figure 1: Configuring the ANOVA Streamlined
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Close the List Manager
Select the newly created list (it will be a child of the HuGeneST file)
Select Pathway Analysis from the Biological Interpretation section
Use the default settings (Figure 2)
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Figure 2: Pathway Analysis
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Click Next
Again, use the default settings (Figure 3)
Figure 3: Pathway Enrichment
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Click Next
Select the database required from the drop down menu (circled red in Figure
4 below) – KEGG and Reactome are available
Select the species required (human in this example)
Ensure the column containing the Gene Symbol is correct
Optionally you can include the ANOVA table to parse in Pathway. This
enables you to additionally visualize fold-changes or p-values for all genes
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inside the pathways which are targeted by the array you used, even if they
are not significant (and therefore not in your selection).
Figure 4: Species
If you use Pathway on the selected species for the first time, Pathway will automatically
download the Kegg information needed for the analysis. Once the pathway enrichment
calculation has been performed a new spreadsheet is created (Pathway-Enrichment.txt)
and Partek Pathway will be launched (Figure 5)
Figure 5: Partek Pathway
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The default pathway to be visualized is that with the highest enrichment score – for
confirmation, examine the pathway in row 1 in GS (Figure 6) to confirm “GABAergic
synapse” as the most enriched pathway:
Figure 6: Pathway Enrichment Spreadsheet
Note that this sheet is also included in Pathway.
For each Pathway in the Enrichment spreadsheet it is now possible to perform several
actions. Right-click on the row header to invoke the contextual menu (Figure 7):
Figure 7: Pathway options
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Export genes in Pathway will create a new spreadsheet in Genomics Suite as a
child of the Enrichment spreadsheet – it contains all of the genes from the selected
pathway.
Export genes in list and in pathway creates a smaller list of only the genes from
your list that are present in the selected pathway.
Show Pathway opens the selected pathway in Partek Pathway.
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Description of “Score” columns in the Enrichment sheet:
Enrichment Score
Tissue/Replicate
Score
The negative natural log of the enrichment p-value derived from
the contingency table (Fisher’s Exact test) or the Chi-square test
For each factor in the data a separate score is calculated. This is
derived from the negative log (base 10) of the average p-value for
genes within the pathway for each factor, respectively. A high
score indicates that the genes which fall into the pathway have a
low p-value for the given factor (i.e. display a greater degree of
differential expression)
When assessing the results both the Enrichment Score and the “Factor” Score should be
used. While you will intuitively want to sort by the Enrichment Score (indeed Pathway
sorts by this column as the default option) this can sometimes be misleading. For
example, if the number of genes in the entire pathway is small it only takes a few genes
being differentially expressed to give a high Enrichment Score. If the same number of
genes is differentially expressed in a pathway with many more genes the Enrichment
Score will be lower. This is where the “Factor” Score can be particular informative: if
two pathways have same similar Enrichment Scores, how can you interpret this? A higher
“Factor” Score indicates a greater average degree of differential expression, thus this
pathway is potentially more interesting..
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Pathway
The Project Elements pane displays the current pathway (in this case the most enriched
pathway), the original gene list (significant genes between brain and heart), the Pathway
Enrichment spreadsheet (as highlighted in Figure 6 above), and the Library References
used (Figure 8).
Figure 8: Project Elements
In the event the Pathway libraries are not downloaded, click on the “Pathway Libraries”
icon (circled in Figure 8) – you can now download available libraries, or choose specific
pathways from libraries that have already been downloaded (Figure 9).
Figure 9: Manually adding Libraries/Pathways
It is also easy to open additional pathway diagrams from the Enrichment table:
• Select the Pathway-Enrichment list (Figure 10)
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Figure 10: Opening additional pathways in the enrichment table
Note: It is also possible to sort any of the tables within Pathway, simply by clicking on
the column header. The first click will sort ascending, while the second will sort
descending.
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Click on a Pathway ID to open the diagram (Figure 11)
Figure 11: Viewing additional pathways
The pathways can also be searched for known genes/genes of interest.
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Open the search tools be clicking the +/- button (bottom left corner of Figure 12)
Select the species/libraries to be searched (note that in this example both mouse
and human for both KEGG and Reactome are searchable)
Type the search term (gene symbol) into the search box and press enter
In the Search Results window all pathways containing the gene symbol will be
shown
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Double-click on a pathway to open it
Figure 12: Searching pathways for a gene of interest
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With a pathway diagram open it is now possible to colour the genes by various
factors, such as p-value or fold-change – see the “Configuration” pane in the
upper right corner (Figure 13). By default the map is coloured by the first p-value
(“Tissue” in the this example)
If you have checked to include the original ANOVA table during invoking
Pathway (see above), you will the additional columns in the list below the Brain
vs Heart columns.
Figure 13: Colour by…
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To illustrate, return to the Pathway Enrichment list and open the 6th most
enriched pathway (Long-term potentiation) by double-clicking
From the Colour By drop-down select “Fold-Change” – the pathway will now be
coloured (Figure 14)
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Figure 14: Pathway coloured by Fold-Change
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One gene in the pathway is up-regulated (green) – this gene is AMPAr. To learn
more about the gene, right click to invoke the contextual menu (Figure 15) – you
now have options to link out to KEGG, to External Links (Ensemble or UniProt),
or to jump to the gene in the original list. (Note that the gene in the list is GRIA2
– this is a synonym of AMPAr)
Figure 15: Additional information
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Finally, the Pathway Detail pane (bottom left) show additional information
relating to the selected pathway, and the genes within it (Figure 16)
Figure 16: Pathway Elements
End of Tutorial
The steps covered in this tutorial are:
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Generating a Pathway Enrichment spreadsheet in GS
Viewing the results in Partek Pathway
Sorting and searching Pathway results
For additional assistance, contact our technical support staff by phone at +1-314878-2329 or by email [email protected].
Copyright © 2011 by Partek Incorporated. All Rights Reserved. Reproduction of this material without express written
consent from Partek Incorporated is strictly prohibited.
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