Farida Akhtari

Senior Researcher, National Institute of Environmental Health Sciences (NIH - NIEHS)

5 active projects

prs

Common workspace for multiple PRS analyses. The files in this workspace are common data files and scripts that will be shared across multiple disease-specifie workspaces that do PRS analyses.

Scientific Questions Being Studied

Common workspace for multiple PRS analyses. The files in this workspace are common data files and scripts that will be shared across multiple disease-specifie workspaces that do PRS analyses.

Project Purpose(s)

  • Ancestry

Scientific Approaches

We will use Hail, plink and LDpred2 to compute PRS for multiple phenotypes using the common scripts in this workspace.

Anticipated Findings

We aim to compute PRS for multiple phenotypes in the AoU cohort and show similarities or differences across different phenotypes, gender, ancestries, etc.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Farida Akhtari - Senior Researcher, National Institute of Environmental Health Sciences (NIH - NIEHS)

T2D PRS

The goal of this research is to compute polygenic risk score (PRS) for Type 2 diabetes in the AllofUs Cohort and examine its predictive power for the disease.

Scientific Questions Being Studied

The goal of this research is to compute polygenic risk score (PRS) for Type 2 diabetes in the AllofUs Cohort and examine its predictive power for the disease.

Project Purpose(s)

  • Disease Focused Research (type 2 diabetes)
  • Ancestry

Scientific Approaches

We will be using the EHR data, the whole-genome sequence data and the demographics data from the AllofUs CDR. We will use LDpred2 to compute PRS.

Anticipated Findings

We hope to show that PRS is predictive of Type 2 diabetes risk in the entire AllofUs cohort and also show any differences and similarities across different ancestry groups.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Farida Akhtari - Senior Researcher, National Institute of Environmental Health Sciences (NIH - NIEHS)

Duplicate of How to Work with All of Us Genomic Data (Hail - Plink)(v6)

Not applicable - these notebooks demonstrate example analysis how to use Hail and PLINK to perform genome-wide association studies using the All of Us genomic data and phenotypic data.

Scientific Questions Being Studied

Not applicable - these notebooks demonstrate example analysis how to use Hail and PLINK to perform genome-wide association studies using the All of Us genomic data and phenotypic data.

Project Purpose(s)

  • Disease Focused Research (type 2 diabetes)
  • Other Purpose (Demonstrate to the All of Us Researcher Workbench users how to get started with the All of Us genomic data and tools. It includes an overview of all the All of Us genomic data and shows some simple examples on how to use these data.)

Scientific Approaches

Not applicable - these notebooks demonstrate example analysis how to use Hail and PLINK to perform genome-wide association studies using the All of Us genomic data and phenotypic data.

Anticipated Findings

Not applicable - these notebooks demonstrate example analysis how to use Hail and PLINK to perform genome-wide association studies using the All of Us genomic data and phenotypic data.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Farida Akhtari - Senior Researcher, National Institute of Environmental Health Sciences (NIH - NIEHS)

Duplicate of Phenotype - Type 2 Diabetes (v6)

The Notebooks in this Workspace can be used to implement well-known phenotype algorithms in one’s own research.

Scientific Questions Being Studied

The Notebooks in this Workspace can be used to implement well-known phenotype algorithms in one’s own research.

Project Purpose(s)

  • Educational
  • Methods Development
  • Other Purpose (This is an All of Us Phenotype Library Workspace created by the Researcher Workbench Support team. It is meant to demonstrate the implementation of key phenotype algorithms within the All of Us Research Program cohort.)

Scientific Approaches

Not Applicable

Anticipated Findings

By reading and running the Notebooks in this Phenotype Library Workspace, researchers can implement the following phenotype algorithms:

Jennifer Pacheco and Will Thompson. Northwestern University. Type 2 Diabetes Mellitus. PheKB; 2012 Available from: https://phekb.org/phenotype/18

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

  • Farida Akhtari - Senior Researcher, National Institute of Environmental Health Sciences (NIH - NIEHS)

Collaborators:

  • Jasmine Mack - Graduate Trainee, National Institute of Environmental Health Sciences (NIH - NIEHS)

GxE factors for common diseases

The goal of my research project is to identify genetic and environmental factors influencing complex human disease phenotypes by analyzing high-throughput data using complex statistical and machine learning models. Initially, I will be exploring the AllofUs data to understand, collate…

Scientific Questions Being Studied

The goal of my research project is to identify genetic and environmental factors influencing complex human disease phenotypes by analyzing high-throughput data using complex statistical and machine learning models. Initially, I will be exploring the AllofUs data to understand, collate and QC the various data components and formalize several research questions to better understand the etiology of common complex diseases. For multiple common complex diseases, I will be conducting various analyses to identify the genetic and environmental factors influencing these traits and diseases. I will employ complex statistical methods to identify GxE interactions for multiple traits and diseases. I will also conduct variance decomposition analyses to identify and quantify the contribution of genetic, environmental and GxE factors to multiple traits and diseases.

Project Purpose(s)

  • Disease Focused Research (common complex diseases)
  • Ancestry

Scientific Approaches

We will create cohort datasets for each of the complex traits and diseases to be studied based on inclusion/exclusion criteria specific for the trait/disease under analyses. We will use complex statistical methods including linear or logistic regression, tree-based methods such as random forests, penalized regression methods and advanced machine learning methods as appropriate for the dataset and the hypotheses under test.

Anticipated Findings

We hope that our research and analyses will lead to the identification of novel genetic and environmental factors influencing multiple common complex diseases and traits. We hope to improve our understanding of the etiology of common complex diseases by identifying and quantifying the contribution of genetic, environmental and GxE factors to these traits and diseases.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Farida Akhtari - Senior Researcher, National Institute of Environmental Health Sciences (NIH - NIEHS)
1 - 5 of 5
<
>
Request a Review of this Research Project

You can request that the All of Us Resource Access Board (RAB) review a research purpose description if you have concerns that this research project may stigmatize All of Us participants or violate the Data User Code of Conduct in some other way. To request a review, you must fill in a form, which you can access by selecting ‘request a review’ below.