Olink

Olink®
Part of Thermo Fisher Scientific

Data Ecosystem
Design your proteomics study with confidence

Empower your research from the start. Plan your Olink proteomics study with tools and expert support that help you select the best panel, estimate sample needs, and achieve meaningful results.

Data journey

Where study design fits in your data journey

Study design is the foundation of the proteomics data journey. This stage helps you define research questions, explore biomarkers and pathways, select the right panel, estimate sample size, and plan analysis so downstream data generation, integration, and interpretation deliver meaningful results.

Study Design

Plan your proteomics study with the right design, sample strategy, and endpoints for confident downstream analysis.

Data Generation & QC

Generate high-quality NPX data and apply robust QC so results are reliable before integration and comparison.

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Data Integration & Normalization

Move beyond isolated datasets—normalize and bridge NPX data, connect to population-scale cohorts, and compare across studies.

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Data Interpretation

Interpret findings with annotation tools, statistical methods, and expert guidance from Olink Data Science Services.

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    Study design
    From research questions to study plan

    Thoughtful study design helps you make the most of your valuable samples and generate data that supports meaningful breakthroughs. Move from an initial study question to a more informed proteomics study plan with.

    Five useful steps to plan your proteomics study

    Study design step

    What to consider

    Step 1: Define your research question

    Start with the disease area, biological pathway, or protein list relevant to your study needs to address.

    Step 2: Explore biomarkers & pathways

    Review relevant proteins, pathway context, and disease associations to understand what biology your study should capture.

    Step 3: Select the right proteomics solution

    Identify the right proteomics solution that best matches your research question, sample type, and study parameters.

    Step 4: Estimate study size

    Use expected effect size and statistical power considerations to estimate the number of samples needed for confident interpretation.

    Step 5: Move toward data generation

    Proceed with greater confidence into data generation, QC, analysis, and interpretation with your clear study plan in place.

    Study design factors

    Study objective

    Define what your proteomics data should help you explore, such as biomarker discovery, pathway biology, disease mechanisms, or protein changes associated with treatment or response.

    Study groups

    Plan study groups carefully by selecting appropriate controls and comparison groups based on disease statement, treatment exposure, cohort characteristics, or other relevant study variables.

    Sample size

    Estimate the expected effect sizes and the number of samples required to achieve adequate statistical power for the questions being asked.

    Panel selection

    Choose an Olink panel that covers established and exploratory proteins, relevant pathways, and biological functions connected to your research questions. Also, prioritize proteins with low normal variation ranges in healthy subjects.

    Analysis plan

    Make a plan for how normalization, statistical analysis, and bioinformatics will be carried out so the study design supports robust conclusions and meaningful interpretations.

      Olink apps
      Apps to support at every step of your proteomics journey

      From strategic study planning to actionable insights from your proteomic data, Olink apps deliver a comprehensive suite of tools tailored to accelerate your protein analysis-to-conclusions journey.

      Study design

      Select the best panel for your study and optimize the experimental design.

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      Biostatistical analysis

      Use our data analysis tools to determine the statistical significance of your findings.

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      Data interpretation and analysis

      Let our interactive bioinformatics tools help you derive relevant insights from your protein data and add valuable context.

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      Olink services
      Get guided expert support for study design

      New to proteomics or planning a complex study? Let our Olink Data Services team help.

      What Olink Data Services provides:

      • Early consultation: Involve Olink experts early to discuss study goals, sample availability, study groups, and key design considerations.
      • Tailored study guidance: Get support tailoring sample size and statistical power based on your research question.
      • End-to-end perspective: Olink experts help you plan for data analysis to ensure a well-designed, adequately powered protein biomarker study.
      • Data science training: Training sessions to accelerate your transition from proteomic data to biological insights.
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      Get support designing your Olink study

      Work with our Olink data sciences experts to take your proteomics study to the next level, enabling new discoveries and relevant insights.

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