Seminar Series

The Applied Biostatistics Seminar Series consists of a series of talks with the primary purpose of furthering statistical knowledge on an applied level. Talks will focus on advances in biostatistical methods and statistical programming techniques and their translation into addressing biomedical research questions. The seminars are open to all members of the Duke community, but primarily geared toward applied statistical researchers.

Novel bioinformatics methods to study structural variants by long-read sequencing

Kai Wang, PhD
Friday, October 25, 2019 - 11:00 at MSRB I #01

Abstract: It is known that pathogenic structural variants (SVs) might be missed by short-read sequencing, potentially contributing to the low diagnostic rates (~30-40%) in clinical genome/exome sequencing. To address these challenges, we are developing novel bioinformatics methods to detect SVs from long-read sequencing data. In the talk, I will describe...
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eQTL mapping using RNA-seq data, assumptions, implementations, and cautions

Wei Sun, PhD
Friday, October 11, 2019 - 01:00 at MSRB 3 1125 Seminar Room

Using information from allele-specific gene expression (ASE) can sub-stantially improve the power for mapping gene expression quantitative trait loci (eQTL). A few methods have been proposed towards this end. We compare these methods and demonstrate the limitations and ad-vantages of each method. We will also discuss our recent work on...
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Towards a Self-Learning EHR System

Tianxi Cai, PhD
Friday, September 20, 2019 - 11:00 at MSRBI #001

The wide adoption of electronic health records (EHR) systems has led to the availability of large clinical datasets available for discovery research. EHR data, linked with bio-repository, is a valuable new source for deriving real-word, data-driven prediction models of disease risk and progression. Yet, they also bring analytical difficulties. Precise...
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Mapping robust trans-associations via cross-condition mediation analyses and validating trait-associations of trans-genes for GWAS SNPs

Lin Chen, PhD
Friday, September 6, 2019 - 10:00 at 8065 Hock Plaza

Abstract: Trans-eQTLs explain a substantial proportion of expression variation, yet are challenging to be detected and replicated since their effects often act in a tissue-specific manner. Many trans-effects are mediated via cis-gene expression and some of those effects are shared across tissue types/conditions. In order to detect robust cis-mediated trans-associations,...
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Graphical Models for Gene Regulation

Wednesday, August 7, 2019 - 11:00 at MSRB III 1125

Abstract: Probabilistic graphical models provide a flexible means of integrating multiple sources of information while accounting for known dependencies and other prior knowledge. Implementing such models is now considerably easier than before, due to the availability of frameworks such as STAN that automate the inference task for a given model...
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