AWS Healthomics Integration

Platform Overview Basepair is a cloud-based bioinformatics platform designed to streamline genomic data analysis for clinical and research labs. It enables users to upload raw sequencing data, run customizable pipelines, and generate interactive reports — all from a user-friendly interface.

Key Benefits

Accelerated genomic analysis workflows
- Simplified team collaboration and access control
- Seamless integration with cloud storage and analysis environments
- Intuitive data sharing and management
- Automated and reproducible pipelines

Supported File Types

HealthOmics supports the following file types:

FASTQ: View Sample
BAM: View Sample
CRAM: View Sample

Basepair integrates with AWS HealthOmics to provide access to additional pipelines, scalable infrastructure, and seamless interoperability with genomic workflows.
Uploading Samples to HealthOmics

The upload process mirrors Basepair’s standard flow, with a key consideration Genome field
For FASTQ files: Any genome can be selected.
For BAM/CRAM: The genome must match the file's reference genome.
HealthOmics allows a maximum of 5 concurrent sample imports. Additional samples are queued.

The GUI does not explicitly show whether a sample resides in HO or S3.

Identifying HealthOmics Samples is uploaded to HealthOmics or not:

To verify if a sample was uploaded to HealthOmics:
Status Indicator:
During import: ho_import_in_progress
Once complete: completed

4.1. Sample URI Format:

Basepair S3:
s3://basepair/uploads/7819/101233/3d06.fasta

HealthOmics S3:
s3://613396392907-.../sequenceStore/.../readSet/.../Control1_L001_R1.fastq.gz

Note: Currently, the GUI does not explicitly show whether a sample resides in HO or S3

Running a HealthOmics Analysis

Select a Ready-2-Run or Private Workflow from HealthOmics.

Choose the relevant sample.

Provide any required parameters.

Once configured, an analysis will be launched on both Basepair and HealthOmics platforms.

Example Analyses

Ready-2-Run Workflow: View Analysis
Private HealthOmics Workflow: View Analysis
Basepair Workflow: View Analysis
Interactive Report Example: View Report
Creating a Private HealthOmics Workflow

You can create your own custom workflows on AWS HealthOmics and manage them via the Basepair platform.

Steps to Create a Private Workflow

Navigate to Pipelines > Create New AWS HealthOmics Workflow.

Fill in the required fields:

Workflow Name

Description

Run Storage Capacity

Workflow Definition (ZIP format)

Workflow Language

(Optional) Main Workflow Definition File Path

Workflow Visibility (Private/Public)

Input Parameters

Important Notes:

The workflow definition file must be a zip
2. If we select an incorrect workflow language then Workflow creation will fail
3. The visibility field states the visibility of workflow.
4. If private it will be visible to the Owner of workflow only.
5. If public it will be visible to all the users on the host.
6. Workflow creation will fail if we specify an incorrect Main workflow definition file path
7. The parameters state the parameters expected during the run time.
8. We can create max 100-private workflow
9. Workflow is created on HealthOmics only if it's created successfully.
10. Max file for zip is 4.4Mb
Creating a HealthOmics Reference Genome

You can create and import reference genomes into HealthOmics directly from Basepair.

Steps:

Go to the Samples tab and select Add Genome.

Enter a unique genome name and upload your genome file.

Once uploaded to S3, ho_import begins automatically.

Status will be marked as Completed once the genome is imported successfully.

You can also add genome-level parameters during setup.

Importing AWS HealthOmics Workflows into Basepair:
Step 1: Discover Available Workflows

Navigate to Pipelines > AWS HealthOmics Workflows

All workflows from your AWS account will be listed

Step 2: Sync a Workflow

Click the Sync button to import the workflow and its parameters

Sync status will show ✅ Yes once successful

Step 3: Configure Parameters

Go to Pipelines > Basepair HealthOmics Workflows > [Your Synced Workflow] > Edit

For each parameter, define how it behaves:
- Sample URI: Auto-populated from uploaded sample
  - Fixed Value: Hardcoded, hidden from users
  - Custom: User-editable during analysis setup
  - Add/Edit Descriptions:
  - Descriptions are editable
  - Tooltips support multiline text and special characters

8.4. Step 4: Select Storage Type

When creating or updating a workflow, select Dynamic Storage Option to enable flexible AWS HealthOmics storage support.