Yingchang Lu

Early Career Tenure-track Researcher, Vanderbilt University Medical Center

14 active projects

Duplicate of Duplicate of Phenotype - Ischemic Heart Disease (v7)_MI

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:

Christianne L. Roumie; Jana Shirey-Rice, Sunil Kripalani. Vanderbilt University. MidSouth CDRN - Coronary Heart Disease Algorithm. PheKB; 2014. Available from https://phekb.org/phenotype/234

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

  • Yingchang Lu - Early Career Tenure-track Researcher, Vanderbilt University Medical Center

Multivariate analysis of metabolic traits

Few genome-wide association studies of metabolic traits were performed in populations of African ancestry. The studies performed so far were of small sample sizes. We want to perform the largest genome-wide association studies of metabolic traits in populations of African…

Scientific Questions Being Studied

Few genome-wide association studies of metabolic traits were performed in populations of African ancestry. The studies performed so far were of small sample sizes. We want to perform the largest genome-wide association studies of metabolic traits in populations of African ancestry.

Project Purpose(s)

  • Disease Focused Research (metabolic traits)
  • Ancestry

Scientific Approaches

We want to apply novel multivariate methods of meta-analyzing summary statistics of metabolic traits in populations of African ancestry to boost the discovery power.

Anticipated Findings

The largest genome-wide association studies of metabolic traits in populations of African ancestry will help understand the genetic determinants of these metabolic traits and potentially reveal novel biology of these traits.

Demographic Categories of Interest

  • Race / Ethnicity

Data Set Used

Controlled Tier

Research Team

Owner:

  • Yingchang Lu - Early Career Tenure-track Researcher, Vanderbilt University Medical Center

Collaborators:

  • Jaehyun Park - Research Fellow, Vanderbilt University Medical Center

Duplicate of Phenotype - Ischemic Heart Disease (v7)

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:

Christianne L. Roumie; Jana Shirey-Rice, Sunil Kripalani. Vanderbilt University. MidSouth CDRN - Coronary Heart Disease Algorithm. PheKB; 2014. Available from https://phekb.org/phenotype/234

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

  • Yingchang Lu - Early Career Tenure-track Researcher, Vanderbilt University Medical Center

Heart Disease AllofUs WGS analysis

The incidence of coronary artery disease in populations of African ancestry is higher than that in populations of European ancestry. Besides the social economic risk factors, behavior risk factors, and access to health care, the genetic factors may underlie the…

Scientific Questions Being Studied

The incidence of coronary artery disease in populations of African ancestry is higher than that in populations of European ancestry. Besides the social economic risk factors, behavior risk factors, and access to health care, the genetic factors may underlie the observed this health disparity. Hundreds of genetic loci have been identified in genome-wide association studies of coronary artery disease in populations of European ancestry and populations of Eastern Asian ancestry. However, very few loci were identified in populations of African ancestry. This may create the hurdles of equal utilization of precision medicine in control and prevention of coronary artery disease across populations. We will perform the large genome-wide association study of coronary artery disease in populations of African ancestry.

Project Purpose(s)

  • Disease Focused Research (coronary artery disease)
  • Ancestry

Scientific Approaches

We will perform a whole genome sequence analysis of coronary artery disease with allofus electronic health record data.

Anticipated Findings

We will identify genetic loci associated with coronary artery diseases in populations of African ancestry that shared with populations of other ancestries or are unique to populations of African ancestry due to its unique demographic and evolutionary history. The novel biology elucidated from the identified loci will help with the control and prevention of coronary artery disease across all populations.

Demographic Categories of Interest

  • Race / Ethnicity

Data Set Used

Controlled Tier

Research Team

Owner:

  • Yingchang Lu - Early Career Tenure-track Researcher, Vanderbilt University Medical Center

Duplicate of Intro to AoU Fitbit Data - Short Course Labs - 07212023 (v7)

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Scientific Questions Being Studied

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Project Purpose(s)

  • Educational
  • Methods Development

Scientific Approaches

Not Applicable

Anticipated Findings

...

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

  • Yingchang Lu - Early Career Tenure-track Researcher, Vanderbilt University Medical Center

Duplicate of Intro to AoU Fitbit Data - Short Course Labs - 07212023 (v7)

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Scientific Questions Being Studied

...

Project Purpose(s)

  • Educational
  • Methods Development

Scientific Approaches

Not Applicable

Anticipated Findings

...

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

  • Yingchang Lu - Early Career Tenure-track Researcher, Vanderbilt University Medical Center

Duplicate of Workshop: Intro to All of Us Genomics Data

This workspace is meant to help researchers get familiar with the All of Us Researcher Workbench. There are five hands-on exercises during the workshop, each with a specific notebook. Exercise 1: Duplicate the workspace & start the cloud environment Exercise…

Scientific Questions Being Studied

This workspace is meant to help researchers get familiar with the All of Us Researcher Workbench. There are five hands-on exercises during the workshop, each with a specific notebook.
Exercise 1: Duplicate the workspace & start the cloud environment
Exercise 2: Looking at the genomic data (notebook)
Exercise 3: GWAS - extracting phenotypic data (notebook)
Exercise 4: GWAS - running Hail GWAS (notebook)
Exercise 5: Advanced GWAS (2 notebooks)

By running the exercises in this workspace, researchers will become more familiar with the genomic data, know how to access the genomic data, see how the genomic data and tools can be used in the Researcher Workbench, and be able to start their own genomic data project.

Project Purpose(s)

  • Other Purpose (This workspace is meant for use during the Introduction to Analyzing All of Us Genomic Data workshop. In this workshop, participants will get hands-on experience using the genomics data running a genome-wide association study (GWAS) using Hail. )

Scientific Approaches

We are using the All of Us dataset in order to run a genome-wide association study (GWAS) using Hail. In the workshop, we will give an introduction to the All of Us Researcher Workbench and demonstrate how to use the Cohort Builder and Jupyter Notebooks to set up a research project. Using Jupyter notebooks, we will create a dataset linking the All of Us phenotypic data to the short read whole genome sequencing (srWGS) data. After running the GWAS steps using Hail, we will visualize the results.

Anticipated Findings

This study is running a genome-wide association study (GWAS) using Hail, using height as the selected phenotypic data. We do not anticipate findings from this example workspace but we expect that workshop participants will be able to apply similar methods to their future research.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Yingchang Lu - Early Career Tenure-track Researcher, Vanderbilt University Medical Center

Duplicate of CQS Short Course EHR Module

The purpose of this workspace is to provide an overview of the OMOP Common Data Model to registered researchers interested in working with EHR data.

Scientific Questions Being Studied

The purpose of this workspace is to provide an overview of the OMOP Common Data Model to registered researchers interested in working with EHR data.

Project Purpose(s)

  • Educational

Scientific Approaches

I will demonstrate how to find concepts on the Researcher Workbench using several strategies: concept_id, concept_code, concept_name, and source_concept_id.

Anticipated Findings

After this tutorial, I hope the students will have a better understanding of how to work with EHR data on the Researcher Workbench.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Yingchang Lu - Early Career Tenure-track Researcher, Vanderbilt University Medical Center

Duplicate of Demo - Family History in EHR & PPI Data

As a demonstration project, this study will summarize structured data elements available in the All of Us registered tier and compare to published survey results to describe data for reuse in disease specific outcomes. Specific questions include: 1. Could harnessing…

Scientific Questions Being Studied

As a demonstration project, this study will summarize structured data elements available in the All of Us registered tier and compare to published survey results to describe data for reuse in disease specific outcomes. Specific questions include:

1. Could harnessing informatics tools like predictive modeling and clinical decision support to detect and alert healthcare providers to these preventative measures significantly improve the precise care we deliver to patients?
2. How can one evaluate the availability of family medical history information within the All of Us registered tier data and characterize the structured data elements from both data sources?

Project Purpose(s)

  • Methods Development
  • Other Purpose (This work is a result of an All of Us Research Program Demonstration Project. The projects are efforts by the Program designed to meet the program's goal of ensuring the quality and utility of the Research Hub as a resource for accelerating discovery in science and medicine. This work was reviewed and overseen by the All of Us Research Program Science Committee and the Data and Research Center to ensure compliance with program policy, including policies for acceptable data access and use.)

Scientific Approaches

We utilize the Family Medical History PPI survey to capture self-reported information but exclude participants who did not know any of their family history or who skipped every survey question. We pay particular attention to the disease/relative pairings that map to the American College of Medical Genetics and Genomics’ (ACMG) list of important diseases.

We define EHR family history information as the collection of registered tier observations with "family+history" or "FH:" anywhere in their OMOP concept name. We exclude observations of “Family social history” and remove duplicate observation and value concept pairings from the same healthcare organization regarding the same participant as these were likely due to repeated entries across multiple routine annual physical exams.

We aim to compare the data sources by summarizing the type and amount of family history information gained.

Anticipated Findings

This description of the family medical history data in the All of Us registered tier database will assist future investigators in understanding All of Us data methods and give feedback to the program on the utility of participant survey and EHR data.

We hypothesize that the survey data will provide a more complete look at family medical history due to its structured nature. Though, we are also interested in determining how much overlap there is between the PPI and EHR data. It’s plausible that the free-form nature of EHR family history information yields more detailed records. We would ultimately like to determine if a gold standard method for defining a participant’s family medical history is attainable within the All of Us registered tier data.

We anticipate facing informatics challenges because of collecting data from different sources, mapping these data to a common data model, and attempting to harness data from these sources to find the common source of truth.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

  • Yingchang Lu - Early Career Tenure-track Researcher, Vanderbilt University Medical Center

Duplicate of Intro to AoU Fitbit Data - Short Course Labs - 07212023 (v7)

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Scientific Questions Being Studied

...

Project Purpose(s)

  • Educational
  • Methods Development

Scientific Approaches

Not Applicable

Anticipated Findings

...

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

  • Yingchang Lu - Early Career Tenure-track Researcher, Vanderbilt University Medical Center

Duplicate of How to Work with All of Us Survey Data (v7)

We recommend that all researchers explore the notebooks in this workspace to learn the basics of All of Us Program Data. What should you expect? By running the notebooks in this workspace, you should get familiar with how to query…

Scientific Questions Being Studied

We recommend that all researchers explore the notebooks in this workspace to learn the basics of All of Us Program Data.

What should you expect?
By running the notebooks in this workspace, you should get familiar with how to query PPI questions/surveys, what the frequencies of answers for each question in each PPI module are.

Project Purpose(s)

  • Educational
  • Methods Development
  • Other Purpose (This is an All of Us Tutorial Workspace created by the Researcher Workbench Support team. It is meant to provide instruction for key Researcher Workbench components and All of Us data representation.)

Scientific Approaches

By running the notebooks in this workspace, you should get familiar with how to query PPI questions/surveys, what the frequencies of answers for each question in each PPI module are.

Anticipated Findings

By reading and running the notebooks in this Tutorial Workspace, researchers will learn the following:
- how to query the survey data,
- how to summarize PPI modules, and questions.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

  • Yingchang Lu - Early Career Tenure-track Researcher, Vanderbilt University Medical Center

Duplicate of Beginner Intro to AoU Data and the Workbench (v7)

This workspace contains multiple notebooks that assess users' understanding of the workbench and OMOP. These notebooks are meant to help users check their knowledge not only on Python, R, and SQL, but also on the general data structure and data…

Scientific Questions Being Studied

This workspace contains multiple notebooks that assess users' understanding of the workbench and OMOP. These notebooks are meant to help users check their knowledge not only on Python, R, and SQL, but also on the general data structure and data model used by the All of Us program.

Project Purpose(s)

  • Educational

Scientific Approaches

There are no scientific approach used in this workspace because it is meant for educational purposes only. We will cover all aspects of OMOP, and hence will use most datasets available in the workbench.

Anticipated Findings

We do not anticipate to have any findings. Instead, we are educating people on the use of the workbench and the common data model OMOP used by the program.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

  • Yingchang Lu - Early Career Tenure-track Researcher, Vanderbilt University Medical Center

Duplicate of Genomics-Workshop-July2023

This workspace is meant to help researchers get familiar with the All of Us Researcher Workbench. There are five hands-on exercises during the workshop, each with a specific notebook. Exercise 1: Duplicate the workspace & start the cloud environment Exercise…

Scientific Questions Being Studied

This workspace is meant to help researchers get familiar with the All of Us Researcher Workbench. There are five hands-on exercises during the workshop, each with a specific notebook.
Exercise 1: Duplicate the workspace & start the cloud environment
Exercise 2: Looking at the genomic data (notebook)
Exercise 3: GWAS - extracting phenotypic data (notebook)
Exercise 4: GWAS - running Hail GWAS (notebook)
Exercise 5: Advanced GWAS (2 notebooks)

By running the exercises in this workspace, researchers will become more familiar with the genomic data, know how to access the genomic data, see how the genomic data and tools can be used in the Researcher Workbench, and be able to start their own genomic data project.

Project Purpose(s)

  • Other Purpose (This workspace is meant for use during the Introduction to Analyzing All of Us Genomic Data workshop. In this workshop, participants will get hands-on experience using the genomics data running a genome-wide association study (GWAS) using Hail. )

Scientific Approaches

We are using the All of Us dataset in order to run a genome-wide association study (GWAS) using Hail. In the workshop, we will give an introduction to the All of Us Researcher Workbench and demonstrate how to use the Cohort Builder and Jupyter Notebooks to set up a research project. Using Jupyter notebooks, we will create a dataset linking the All of Us phenotypic data to the short read whole genome sequencing (srWGS) data. After running the GWAS steps using Hail, we will visualize the results.

Anticipated Findings

This study is running a genome-wide association study (GWAS) using Hail, using height as the selected phenotypic data. We do not anticipate findings from this example workspace but we expect that workshop participants will be able to apply similar methods to their future research.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Yingchang Lu - Early Career Tenure-track Researcher, Vanderbilt University Medical Center

Duplicate of How to use dsub in the Researcher Workbench (v7)

The purpose of this workspace is to demonstrate how to use dsub within the Researcher Workbench. This workspace will demonstrate writing dsub jobs.

Scientific Questions Being Studied

The purpose of this workspace is to demonstrate how to use dsub within the Researcher Workbench. This workspace will demonstrate writing dsub jobs.

Project Purpose(s)

  • Educational

Scientific Approaches

The purpose of this workspace is to demonstrate how to use dsub within the Researcher Workbench. This workspace will demonstrate writing dsub jobs.

Anticipated Findings

N/A

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Yingchang Lu - Early Career Tenure-track Researcher, Vanderbilt University Medical Center
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