Building a Cohort in Explore

Why use Explore?

The primary purpose of the Explore page in BDC-PIC-SURE is to select participants and variables for analysis.

Accessing and using raw data files for analysis can be challenging, particularly with the diverse range of data file formats and structures that vary according to the study design. The Explore page enables you to search for decoded variable information, apply filters, select variables, and hand off your data in an analysis-ready format—all without needing to handle raw data files.

How to use Explore

1. Log in to BDC-PIC-SURE. To access the Explore page, you will need to be logged in.

2. Search for the terms or variables related to your planned research project. This could include clinical outcomes, phenotypes, demographics, and more.

3. Apply facets to narrow down your search results. Use the left-hand panel to add facets to your search. This could include selecting specific studies or data types of interest.

4. Learn more about the variable by clicking on the row. When you find a promising search result, you can learn more about the variable by clicking on the row or the "i" icon. This will display the study and dataset associated with the variable.

5. Apply filters. Once you have identified variables, you can apply filters by clicking the funnel icon. This will add inclusion criteria, or "filter down" the cohort of participants.

6. Apply genomic filters. Filters can be added to variants in specific genes in combination with phenotypic filters.

7. Include additional variables for analysis. If there are additional variables you would like to include in your dataframe but not apply filters, you can use the "Add to Export" icon, which looks like a square with an arrow pointing right.

8. Bring your data to an analysis platform. Once you have applied filters, selected variables, and built your cohort, you are ready to bring the participant-level data to a BDC analysis platform. Click on the "Prepare for Analysis" button to start the process.

9. Start your analysis! You are now ready to begin analyzing your participant-level data.

Tip: Try searching for different terms.

You may need to try a few different searches to find the expected search results. For example, perhaps your search for "IPF" only returned a few variables. You can also try searching for the full name ("idiopathic pulmonary fibrosis") or related terms (such as "interstitial lung diseases").