Using the Lifenome API

To help developers get started smoothly, we’ve prepared a step-by-step overview of how to use the Lifenome API to create samples, provide genetic data, and generate PDF reports. This serves as a quick guide and complements the detailed documentation available at developers portal .

The process follows a clear sequence, starting from authentication and sample creation, through adding genetic data, and finally to trait assessments and report generation. Below is a detailed walkthrough:

Authenticate

Guide 

Before making any API calls, you must first obtain secure access credentials. Use the API keys you were provided to obtain an access token. All requests use Bearer Token authentication over HTTPS.

Create a Sample

Guide 

Every interaction with genetic data begins by creating a Sample, which acts as the digital record for an end user:

• Every end user is represented in the system as a Sample object.
• Samples hold demographic and lifestyle data and serve as the anchor for genetic data.
• Gender is mandatory if medical traits are used and/or if Labcorp/GxG integration is enabled. Guide 

To set up gender use the following:

curl --request PUT \
  --url "https://myportal.lifenome.com/api/core-api/samples/${SAMPLE_ID}/attributes/" \
  --header "Content-Type: application/json" \
  --header "Authorization: Bearer ${ACCESS_TOKEN}" \
  --data '{"gender": "male"}'

Valid values are: male or female.

Provide genetic data

Once the Sample exists, genetic data must be attached. This can be done either through lab-processed kits or uploaded genotype files.

Option A – DNA Kits (Labcorp / GxG)

Guide 

• Register the kit with the sample.
• The external lab processes the kit.
• Lifenome automatically retrieves genotype data once available.
• Traits and reports are generated when the data is ready.

Option B – File uploads

Guide 

• Upload a genotype file in a supported format (23andMe, Ancestry, VCF, GxG, Labcorp).
• Create a Genotype object and link it to the sample.
• The file is parsed and trait computations start automatically.

Note: Processing is asynchronous. Use status endpoints to check readiness before fetching traits or generating reports.

Access traits

Guide 

After the genetic data has been processed, the platform generates trait-level insights.

• Once genetic data is processed, the platform computes trait assessments.
• These may include risk levels, polygenic scores, and coverage metrics.
• The exact trait set depends on tenant configuration.

Generate PDF reports

Guide 

The final step is to compile all trait assessments into structured PDF reports for end users.

• Reports summarize assessments in PDF format.
• They can be customized per tenant and include descriptive text and visuals.
• Currently available reports (depending on tenant configuration) are:
  • Nutrinome - Provides personalized nutrition insights based on genetic predispositions related to diet, metabolism, and nutrient needs.
  • Fitnome - Delivers fitness and exercise recommendations tailored to genetic factors influencing endurance, strength, and recovery.
  • Personome - Explores genetic influences on personality, learning abilities, and behavioral tendencies.
  • Allergenome - Highlights genetic predispositions to food and environmental sensitivities that may influence wellness and lifestyle choices.
  • Beautynome - Summarizes skin and aging-related traits with insights for beauty and self-care personalization.
  • Hairnome - Focuses on genetic factors related to hair growth, hair loss, and scalp health to support personalized haircare strategies.
  • Medical report - Summarizes medically relevant traits and predispositions with supporting information for health management and clinical use.
  • Longevity report - Accompanies the Longevity Assessment by summarizing genetic predispositions across wellbeing and medical traits relevant to aging, healthspan, and long-term wellness.

Longevity and other stateless assessments (optional)

Guide 

The platform also supports stateless assessments, primarily for longevity and biological age estimation.

• Use dynamic inputs such as blood biomarkers, methylation data, and lifestyle questionnaires.
• Unlike DNA-based traits, results can be recalculated multiple times as inputs change.
• Data is not stored persistently, making it ideal for monitoring and experimentation.

Summary

The API workflow is:

Authenticate → Create a Sample → Provide genetic data (via DNA kits or file upload) → Access traits → Generate reports → Longevity assessment (optional)