Cohort Browser

Visualize your data and browse your multi-omics datasets.

An Apollo license is required to use Cohort Browser on the DNAnexus Platform. Org approval may also be required. Contact DNAnexus Sales for more information.

Cohort Browser is a visualization tool for exploring and filtering structured datasets. It provides an intuitive interface for creating visualizations, defining patient cohorts, and analyzing complex data.

Cohort Browser supports multiple types of datasets:

• Clinical and phenotypic data - Patient demographics, clinical measurements, and outcomes

• Germline variants - Inherited genetic variations

• Somatic variants - Cancer-related genetic changes

• Gene expressions - Molecular expression measurements

• Multi-assay datasets - Datasets combining multiple assay types or instances of the same assay type

If you need to perform custom statistical analysis, you can also use JupyterLab environments with Spark clusters to query your data programmatically.

Prerequisites

You need to ingest your data before you can access it through a dataset in the Cohort Browser.

Opening Datasets Using the Cohort Browser

1. In Projects, select the project where your dataset is located.

2. Go to the Manage tab.

3. Select your dataset.

4. Click Explore Data.

Selecting a dataset to explore

You can also use the Info Panel to view information about the selected dataset, such as its creator or sponsorship.

Getting familiar with Cohort Browser

Depending on your dataset, the Cohort Browser shows the following tabs:

• Overview - Clinical data using interactive charts and dashboards

• Data Preview - Clinical data in tabular format

• Assay-specific tabs - Additional tabs appear based on your dataset content:

  • Germline Variants - For datasets containing germline genomic variants

  • Somatic Variants - For datasets containing somatic variants and mutations

  • Gene Expression - For datasets containing molecular expression data

Exploring Data in a Dataset

In the Cohort Browser's Overview tab, you can visualize your data using charts. These visualizations provide an introduction to the dataset and insights on the clinical data it contains.

Sample clinical dashboard with multiple tiles and cohorts

When you open a dataset, Cohort Browser automatically creates an empty cohort that includes all records in the dataset. From here, you can add filters to create specific cohorts, build visualizations to explore your data, and export filtered data for further analysis outside the platform.

Next Steps

• Creating Charts and Dashboards - Build visualizations and manage dashboard layouts

• Defining and Managing Patient Cohorts - Filter data and create patient groups

• Analyzing Germline Genomic Variants - Work with inherited genetic variations

• Analyzing Somatic Variants and Mutations - Explore cancer-related genetic changes

• Analyzing Gene Expression Data - Examine molecular expression patterns