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.

Integrative analysis of multi-omics data improves genetic risk prediction and transcriptome-wide association analysis

Yiming Hu
Wednesday, February 28, 2018 - 10:00 at MSRB 1 Room 001 Ground level Classroom

Abstract: Accurate prediction of disease risk based on genetic factors is an important goal in human genetics research and precision medicine. Better prediction models will lead to more effective disease prevention and early treatment strategies. Despite the identification of thousands of disease-associated genetic variants through Genome Wide Association Studies (GWAS)...
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Relatedness and differentiation in arbitrary population structures

Alejandro Ochoa, PhD
Wednesday, February 21, 2018 - 10:00 at MSRB 1 Room 001 Ground level Classroom

Abstract: Several biomedical applications, including genome-wide association studies and heritability estimation for complex traits, require accurate modeling of the covariance structure of genetic variants. This dependence structure is parametrized by kinship coefficients, which are defined as the probability that random alleles are "identical by descent" (IBD). The fixation index "F_ST"...
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Tissue specific transcriptome prediction and gene-level association mapping and fine-mapping

Yongtao Guan, PhD
Friday, February 16, 2018 - 10:00 at Hock Plaza, 2nd Floor CRTP Classroom

Abstract: Tissue-specific gene expressions have direct relevance to disease phenotypes, and knowing gene expression in disease-relevant tissues is advantageous in both detecting novel associations and fine-mapping known genetic associations. Unfortunately, almost all genome-wide association study (GWAS) datasets have no companion gene expression assay, let alone tissue-specific ones. The idea of...
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Computational and Statistical Methods for the Genetic Analysis of the Regulatory Genome.

Roger Pique-Regi, PhD
Monday, February 12, 2018 - 10:00 at MSRB 1 Room 001 Ground level Classroom

Abstract: Learning the gene regulatory grammar encoded in the human genome is a fundamental step in understanding the role of non-coding genetic variation in human phenotypes. My talk will focus on the challenges and methods for analyzing large genomic datasets to study and integrate information on transcription regulation, chromatin state/accessibility,...
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Statistical methods for high-throughput genomic data

Zhixiang Lin, PhD
Monday, February 5, 2018 - 10:00 at MSRB 1 Room 001 Ground level Classroom

Abstract: In the first part of the talk, a dimension reduction method will be introduced where we extend Principal Component Analysis to propose AC-PCA for simultaneous dimension reduction and Adjustment for Confounding variation. We show that AC-PCA can adjust for variations across individual donors present in a human brain dataset...
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