Courses Taught by Sebastian Zoellner

BIOSTAT612: Grad School And Professional Success Skills

  • Graduate level
  • Residential
  • Winter term(s) for residential students;
  • 1 credit hour(s) for residential students;
  • Instructor(s): Hui Jiang, Kelley Kidwell, Sebastian Zoellner, (Residential);
  • Prerequisites: None
  • Description: This course complements the Biostatistics curriculum in providing more tailored content to succeed as a student, on the job market, and professionally on the job. This discussion includes didactic lectures and activities led by instructors and guest speakers.
  • Learning Objectives: Continuation of Biostat 611: Learn skills to survive and thrive as a Biostatistics MS student. Discuss the variety of career opportunities for biostatisticians. Prepare for internship and job opportunities. Learn skills to be a successful professional across a variety of fields.
JiangHui
Hui Jiang
KidwellKelley
Kelley Kidwell
ZoellnerSebastian
Sebastian Zoellner

BIOSTAT666: Statistical Models and Numerical Methods in Human Genetics

  • Graduate level
  • Residential
  • Winter term(s) for residential students;
  • 3 credit hour(s) for residential students;
  • Instructor(s): Sebastian Zoellner (Residential);
  • Prerequisites: Biostat 602 or Perm. Instr.
  • Description: Introduction to current statistical methods used in human genetics. Topics will include sampling designs in human genetics, gene frequency estimation, the coalescent method for simulation of DNA sequences, linkage analysis, tests of association, detection of errors in genetic data, and the multi-factorial model. The course will include a simple overview of genetic data and terminology and will proceed with a review of numerical techniques frequently employed in human genetics.
  • Syllabus for BIOSTAT666
ZoellnerSebastian
Sebastian Zoellner

BIOSTAT865: Advanced Statistical Population Genetics

  • Graduate level
  • Residential
  • Winter term(s) for residential students;
  • 3 credit hour(s) for residential students;
  • Instructor(s): Sebastian Zoellner (Residential);
  • Not offered 2023-2024
  • Prerequisites: None
  • Description: It is an exciting time for research in population genetics. Technological advances are making it increasingly possible to obtain large numbers of genotypes from individuals in a population, and theoretical and algorithmic advances are improving the prospects for obtaining detailed inferences about populations and their evolutionary history. To make use of these dramatic advances in the field, it is important to understand the processes that act on populations and affect the properties of the genotypes that will eventually be drawn from these populations. In this course, by learning the mathematical models used in population genetics, students will learn how various population-genetic phenomena influence the properties of genetic variation. Students will also gain an understanding of the statistical methods used for analysis of population-genetic data. The course is split into two major sections. The first section covers classical population genetics, including subjects first introduced by RA Fisher and S Wright. We cover Hardy-Weinberg equilibrium, natural selection in infinite and finite populations, stochastic effects in finite populations (drift), recombination and linkage disequilibrium, and admixture and population subdivision. Moreover, we cover the most commonly used models of mutation, such as the infinite sites model and the infinite alleles model. The goal of this section is to give students a broad understanding of the statistical principles underlying population genetics and to provide a connection between these classical results and modern challenges in statistical genetics. In the second section of the course we cover coalescent theory. We introduce the basic coalescent model for constant Wright-Fisher populations. We then introduce commonly used extensions of this model to scenarios with recombination, population expansion and population subdivision. We introduce methods of parameter inference based on these models, including both simple method-of-moments estimates as well as more sophisticated Monte-Carlo based estimation methods. The goal of this section is to give students the ability to design realistic simulation algorithms and perform population genetic inference. Classes on population structure and population admixture (~4) will be taught by Noah Rosenberg. In the biweekly homeworks, we expect the students to be able to apply and extend the presented theory. Early in the course, each student will select a topic for a project; the student is expected to work on this project throughout the semester and to give at the end of the semester a written project report and a 20-minute presentation on the results of his analysis. Typical projects are " Simulate a model of rare variants under mutation-selection balance and estimate power for rare variants testing methods. " Calculate the contribution of low frequency variants to heritability in structured populations " Perform a principal components analysis on genetic data " Explore recent resequencing data for signs of natural selection.
  • Learning Objectives: See course description
ZoellnerSebastian
Sebastian Zoellner

BIOSTAT866: Advanced Topics in Genetic Modeling

  • Graduate level
  • Residential
  • Winter term(s) for residential students;
  • 3 credit hour(s) for residential students;
  • Instructor(s): Sebastian Zoellner (Residential);
  • Not offered 2023-2024
  • Prerequisites: Biostat 601, Biostat 602, Biostat 666 or Perm. Instr.
  • Description: Advanced topics in quantitative genetics with emphasis on models for gene mapping, pedigree analysis, reconstruction of evolutionary trees, and molecular genetics experiments, computational mathematics, and statistical techniques such as Chen-Stein Poisson approximations, hidden Markov chains, and the EM algorithm introduced as needed.
  • Syllabus for BIOSTAT866
ZoellnerSebastian
Sebastian Zoellner