Events Calendar

16 Dec
Biostatistics Seminar Tianying Wang,  Assistant Professor at the Center for Statistical Science at Tsinghua University
Event Type

Lectures, Symposia, Etc.

Target Audience

Faculty, Graduate Students, Postdocs

University Unit
Department of Biostatistics
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Biostatistics Seminar Tianying Wang, Assistant Professor at the Center for Statistical Science at Tsinghua University

This is a past event.

Title: Integrated Quantile Rank Test for Heterogeneous Genetic Associations

 

Abstract: Gene-trait associations can be complex due to underlying population heterogeneity, gene-environment interactions, and various other reasons. Existing gene-based tests are mean-based, and may miss or underestimate higher-order associations that could be scientifically interesting. In this talk, we will introduce a new family of gene-level association tests that integrate quantile rank score process to better accommodate complex associations. The resulting test statistics have multiple advantages: (1) they are almost as efficient as the best existing tests when the associations are homogeneous across quantile levels and have improved efficiency for complex and heterogeneous associations, (2) they provide useful insights into risk stratification, (3) the test statistics are distribution-free and could hence accommodate a wide range of underlying distributions, and (4) they are computationally efficient. We established the asymptotic properties of the proposed tests under the null and alternative hypotheses and conducted large-scale simulation studies to investigate their finite sample performance. The performance of the proposed approach is compared with that of conventional mean-based tests through simulation studies and applications to a Metabochip dataset on lipid traits, and to the genotype-tissue expression data in GTEx to identify genes whose expression levels are associated with cis-eQTLs.

 

 

 

Dial-In Information

https://pitt.zoom.us/j/2335387921

Meeting ID: 233 538 7921

Passcode: 2022

Friday, December 16 at 10:00 a.m. to 11:00 a.m.

Virtual Event

Biostatistics Seminar Tianying Wang, Assistant Professor at the Center for Statistical Science at Tsinghua University

Title: Integrated Quantile Rank Test for Heterogeneous Genetic Associations

 

Abstract: Gene-trait associations can be complex due to underlying population heterogeneity, gene-environment interactions, and various other reasons. Existing gene-based tests are mean-based, and may miss or underestimate higher-order associations that could be scientifically interesting. In this talk, we will introduce a new family of gene-level association tests that integrate quantile rank score process to better accommodate complex associations. The resulting test statistics have multiple advantages: (1) they are almost as efficient as the best existing tests when the associations are homogeneous across quantile levels and have improved efficiency for complex and heterogeneous associations, (2) they provide useful insights into risk stratification, (3) the test statistics are distribution-free and could hence accommodate a wide range of underlying distributions, and (4) they are computationally efficient. We established the asymptotic properties of the proposed tests under the null and alternative hypotheses and conducted large-scale simulation studies to investigate their finite sample performance. The performance of the proposed approach is compared with that of conventional mean-based tests through simulation studies and applications to a Metabochip dataset on lipid traits, and to the genotype-tissue expression data in GTEx to identify genes whose expression levels are associated with cis-eQTLs.

 

 

 

Dial-In Information

https://pitt.zoom.us/j/2335387921

Meeting ID: 233 538 7921

Passcode: 2022

Friday, December 16 at 10:00 a.m. to 11:00 a.m.

Virtual Event

Target Audience

Faculty, Graduate Students, Postdocs

University Unit
Department of Biostatistics

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