Services

Genetic Epidemiology

Uncover Insights in Longitudinal & Observational Data

Gain deep insights into disease risk, progression, and treatment response from your longitudinal, time-to-event, and observational data. I can analyze highly complex biomarker datasets, model disease trajectories, identify genetic predictors of treatment response, and quantify the impact of genetic variants on health outcomes. My expertise encompasses a range of statistical methods that can be tailored to your data, including:

  • Time-to-event analysis (e.g., survival analysis, Cox proportional hazards models)

  • Observational analysis (e.g., logistic regression)

  • Methods for handling complex covariance structures in both longitudinal and observational data (e.g., variance components/mixed effects regression models) [1]

Genetic Support Evaluation

Target Validation Made Easy

Understand the full genetic landscape surrounding your potential drug target. My comprehensive target report distills insights from GWAS, exome studies, rare Mendelian diseases, and more. You'll receive a clear, report-card format that facilitates confident decision-making.

GWAS & ExWAS

Identify Genetic Associations with Disease

Uncover genetic variants associated with disease risk and traits through custom GWAS and ExWAS. I can perform comprehensive quality control, imputation, association testing, and fine-mapping analyses. For rare variants, I utilize advanced statistical methods, including burden tests and SKAT, to identify rare variant associations with disease. These analyses can help identify potential drug targets, biomarkers, and personalize treatment strategies.

Single Cell RNA-Seq Analysis

Cutting Edge Analysis, Done Right

Single-cell RNA-Seq promises unprecedented resolution and rich insights for drug discovery [5], but its analysis comes with unique complexities. These datasets involve an unusual level of sparsity and noise and often high computational demands. Using the most appropriate methods and pipelines [6, 7] can overcome these challenges, ensuring robust, statistically sound insights from your data.

Systems Biology Network Analysis

See The Bigger Picture

Expand your target selection strategy beyond isolated genes. I use network analysis to:

  • Map Complex Interactions: Understand how genes within the targeted pathway influence each other, revealing potential synergies and unintended side effects.

  • Predict Efficacy: Identify targets with the highest potential impact on disease mechanisms, leading to more effective therapies.

  • Assess Safety Risks: Anticipate potential on-target toxicity effects by examining how your target interacts with other pathways, leading to the selection of safer options.

Causal Inference

Assess Causality, Inform Drug Development

Strengthen your drug target's causal link to disease. I leverage Mendelian Randomization, a powerful epidemiological method using genetic variants as instrumental variables, to assess the causal relationship between modifiable risk factors (e.g., biomarkers, intermediate phenotypes) and disease outcomes, providing robust evidence for drug target validation and prioritization.

Sample Size & Power Estimation

Success by Design

Before you invest, predict. Using manual epidemiological review of your indication and UKB's rich data, I can calculate the ideal sample size for your genetic association and “omics” studies. This ensures you have the statistical power to detect meaningful results.

Polygenic Risk Scores (PRS)

Unlock the Power of Precision Medicine

Identify individuals most likely to benefit from your therapy by leveraging the predictive power of polygenic risk scores:

  • Stratify Patients: I develop PRS tailored to your drug target, stratifying UKB participants based on their genetic risk for the relevant disease.

  • Refine Clinical Trials: Use PRS to enrich your study population with participants most likely to respond, increasing the chances of demonstrating your drug's efficacy[2, 3].

  • Develop Companion Diagnostics (cDX): PRS insights can guide the development of a genetic test to pair with your therapy, ensuring it reaches the right patients [4].

Custom Phenotype Creation

Pinpoint Your Ideal Patient Population

Don't let generic ICD codes hinder your genomics research. I craft custom, biologically-informed phenotypes by leveraging multimodal UK Biobank data (ICD codes, blood lab results, medication history, proteomics data and more), mirroring your clinical trial endpoints for maximized study relevance. We can also use genetic associations to assess the quality of many phenotypes.

Strategic Consulting

Your Roadmap to Genetic & “Omics” Success

Feeling overwhelmed by the wealth of resources? I’ll guide you through the best tools and strategies for assessing genetic and “omics” evidence to validate and prioritize your drug targets.

Why Choose Gen-Omix?

  • Deep Expertise: I understand the complexities of disease biology, drug discovery, and “omics” data and use rigorous statistical analysis to deliver reliable insights.

  • Tailored Solutions: Your research is unique, and so are my services. I customize the approach to match your specific goals.

  • Focus on Impact: I don't just generate reports; I help you translate them into strategic decisions for your drug development pipeline.

Set up an appointment with me today to discuss how I can empower your research journey!

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