The GDC has many features for analyzing, accessing, and submitting data.
In this video, we will demonstrate some of the features available for working with cohorts, or sets of cases
by creating, managing, and comparing cohorts.
I will demonstrate the process of creating and comparing cohorts in the GDC portal with a few different examples.
In the first example, I want to review the differences between TCGA pancreatic cancer cases with mutations on the KRAS gene
versus those without mutations.
I navigate to the Exploration Page from the main GDC Portal.
On the cases tab, I select ‘Pancreas’ as the primary site and choose TCGA as the program.
I click on the ‘Genes tab’ and add a gene filter for the KRAS gene.
On the right I see that a total of 137 cases in this set have mutations in the KRAS gene.
The set is ready to be saved.
To save the set, I click on the button labeled ‘Save/Edit Case Set’ above the table.
Here I’ll name the set and click save set.
To create the second set of cases without a mutation on the gene,
I can create a set of all the pancreatic cancer cases
and then subtract out those cases without mutations.
I remove the gene filter and save this set of cases.
With this set created, I can add the KRAS filter again
and then choose the “Remove from Existing Case Set”
and choose the previously saved set in order to make a set of cases
without any KRAS mutations.
I can manage the sets by clicking the ‘Manage Sets’ menu at the top.
Here you’ll see a list of saved sets,
including the new sets that I created.
To compare these cohorts, I click on the Analysis tab at the top.
I want to compare the clinical data in my first example
of TCGA pancreatic cancer cases with and without a KRAS mutation.
So I’ll choose Cohort Comparison,
pick the two sets, and click ‘Run’.
On the results page is a survival analysis and comparison of various clinical variables
such as gender and vital status.
I can select which of these variables to view from the menu at the right.
In the next example, I will demonstrate using clinical elements to build cohorts
such as tumor staging information.
I navigate back to the Exploration page and make sure my filters are clear.
This time I choose ‘Kidney’ as the primary site, and ‘TCGA’ as the Program.
To add clinical filters, I click on the ‘Add a Case Filter’ button.
This brings up a dialog that I can use to search for the clinical element of interest.
Since I am interested in tumor stage, I will start typing ‘’tumor".
I then select the clinical element called ‘tumor stage’ which represents the extent of the cancer in the body.
This adds the filter to the cases tab, where I can split the cohort into groups based on this tumor stage.
I will create a cohort of those that have a tumor stage of "ii"
and another that has a tumor stage of "iii"
and then I save the sets in the same as I did way as before.
After having created these sets,
I want to compare the differences between these two cohorts as well
so I navigate back to the Analysis page.
I choose Cohort Comparison,
pick the two sets, and click the 'Run' button to see these differences.
I can see that there is a significant difference in survival between stage ii and stage iii kidney cancer cases.
Not only can I compare the clinical features of these two cohorts,
I can compare the genetic differences as well,
such as which genes are differentially mutated between two cohorts.
In this final example, I want to compare the mutated genes between these two cohorts.
Using the existing sets as a starting point,
I add a gene filter for only the genes that are part of the Cancer Gene Census.
I click on the genes tab to see a list of the mutated genes,
and then I click the ‘Save/Edit Gene Set’ icon to save the set of genes.
I then repeat this process for the other kidney cancer cohort.
To compare the genetic differences between these two cohorts,
I return to the Analysis page from the top menu.
This time I choose 'Set Operations', pick the two gene sets, and click ‘Run’.
On this page, I see an intersection of genes within each cohort displayed in a Venn diagram.
In other words, I see which genes are mutated in both cohorts
and genes that are exclusively mutated in each set.
We can see each set of cases has a unique set of mutated genes
that can be explored further for significance either in the GDC Portal,
or by saving the genes to a separate file.
More information about the GDC Portal including the Cohort Analysis feature can be found on the GDC Documentation site.