• Skip to Content
  • AZ Index
  • Bulletin Home
  • Institution Home
menu
Washington University in St.Louis
2020-21 Bulletin
  • About Us
  • Programs of Study
  • Undergraduate
  • Graduate & Professional
  • Prior Bulletins
  • Search
menu

Biostatistics

  • Bulletin>
  • Graduate & Professional>
  • Medicine>
  • Areas of Study>
  • Biostatistics
Download this page as a PDF
  • Overview
  • Degrees & Offerings
  • Research
  • Faculty
  • Courses

The biostatistics education programs offered by the Division of Biostatistics include three master’s degrees and two graduate certificates: the Master of Science in Biostatistics (MSIBS), the Master of Science in Biostatistics and Data Science (MSBDS), the Master of Science in Genetic Epidemiology (GEMS; for postdocs only), the Certificate in Genetic Epidemiology, and the Certificate in Biostatistics and Data Science. Interested students may pursue individual courses offered by the division.

The Washington University School of Medicine is known for being at the forefront of medical research and primary care; the school engages students in research and practical training so that they can contribute to improving health outcomes. Our programs train students as critical thinkers and collaborators in biostatistics, genetics, and data science. We seek those with undergraduate degrees in the quantitative and biomedical sciences, including fields such as mathematics, statistics, computer science, informatics, and biomedical engineering.

Our programs are designed to teach students how to manage, analyze, and interpret health data using statistical and data science approaches. Internationally renowned faculty from multiple disciplines — including biostatistics, genetics, informatics, medicine, and public health — will train a new generation of quantitative scientists. The curriculum offers a unique training experience that combines core data science learning in statistical and computational methodologies with practical training in real-world data analysis of cutting-edge biomedical and genomics research.

NIH-Sponsored Training Program

The PRIDE Summer Institute in Cardiovascular Genetics and Epidemiology (CVD-CGE) focuses on cardiovascular and other heart, lung, blood, and sleep disorders. This all-expenses-paid summer institute is supported by funding from the National Heart, Lung, and Blood Institute. The goal is to mentor junior faculty from underrepresented minorities as well as faculty with disabilities into independent research careers in the biomedical sciences. For more information, visit the PRIDE CVD-CGE website or email the program administrator.

Academic Calendar

The academic programs begin in early July each year. They start with preparatory workshops, which are followed by intensive summer semester courses. For fall and spring courses, the program follows the Washington University academic calendar. 

Location

The program is located in the Division of Biostatistics, which can be found on the fifth floor of the Bernard Becker Medical Library (660 S. Euclid Ave., St. Louis, MO 63110) in rooms 500 through 508.

Additional Information

Kim Freels
Program Manager
Phone: 314-362-1384
Email: kfreels@wustl.edu

DC Rao, PhD
Program Director
Email: rao@wustl.edu

Lei Liu, PhD
Associate Program Director
Email: lei.liu@wustl.edu

Washington University School of Medicine
Biostatistics Education Programs
Division of Biostatistics
660 S. Euclid Ave., CB 8067
St. Louis, MO 63110-1093

Phone:314-362-1384
Email:biostat-msibs@email.wustl.edu
Website:https://biostatistics.wustl.edu
  • Master of Science in Biostatistics
  • Master of Science in Biostatistics and Data Science
  • Master of Science in Genetic Epidemiology
  • Certificate in Biostatistics and Data Science
  • Certificate in Genetic Epidemiology

Master’s students have multiple opportunities to engage in biomedical research. After completing the first summer semester, students in the MSIBS and MSBDS program are eligible to work as part-time research assistants. These positions are frequently available, both within the Division of Biostatistics as well as in other departments and research labs on the Medical School campus. In addition, depending on the degree program, students will intern and/or work on an independent mentored research project to hone their research skills, including study design, data analysis, and interpretation. GEMS students will work on a mentored research project to explore and characterize the interplay between genes and the environment that affects the biological processes underlying disease.

Division Interim Director

Chengjie Xiong, PhD

Visit our website for more information about our faculty and their appointments.


  • #
  • A
  • B
  • C
  • D
  • E
  • F
  • G
  • H
  • I
  • J
  • K
  • L
  • M
  • N
  • O
  • P
  • Q
  • R
  • S
  • T
  • U
  • V
  • W
  • X
  • Y
  • Z

A

Amber Salter Albright, BS1, PHD, M PH
Assistant Professor of Biostatistics (primary appointment)
Assistant Professor of Neurology
BS1 University of Texas Austin 2002
PHD University of Alabama-Birmingh 2015
M PH University of North Texas Heal 2005

Back to top

C

Ling Chen, PHD, MPH, MS
Assistant Professor of Biostatistics (primary appointment)
Assistant Professor of Medicine
PHD University of MO Columbia 2009
MPH University South Carolina 2003
MS Beijing Medical University 1998
BS Beijing Medical University 1996

Back to top

G

Charles William Goss, PHD, MS
Instructor in Biostatistics (primary appointment)
Instructor in Medicine
PHD Ohio State University 2014
MS Florida International 2018
BS University of Michigan 2003
BA University of Michigan 2018

Chi Gu, PHD, MS
Associate Professor of Biostatistics (primary appointment)
Associate Professor of Genetics
BS Nanjing Medical University 1982
PHD Washington Univ in St. Louis 1992
MS Nanjing Medical University 1985

Aditi Gupta, MS1, PHD
Instructor in Biostatistics (primary appointment)
MS1 UNIVERSITY OF DELHI 2008
PHD Indaprastha Inst. of Informati 2015
BS UNIVERSITY OF DELHI 2005

Back to top

L

Daphne Lew, M PH, PHD, BE, MED
Instructor in Biostatistics (primary appointment)
M PH Saint Louis University 2016
PHD Saint Louis University 2020
BE University of Pennsylvania 2012
MED University of MO St Louis 2014

Lei Liu, PHD, MS2, BS1, MS1
Professor of Biostatistics (primary appointment)
Professor of Medicine
PHD University of Michigan 2017
MS2 Virginia Tech 1998
BS1 ZHEJIANG UNIVERSITY 1994
MS1 ZHEJIANG UNIVERSITY 1997

Back to top

M

J. Philip Miller
Professor of Biostatistics (primary appointment)
Professor of Medicine
Tenure Held At-Large in the Medical School
BA Washington Univ in St. Louis 1965

Back to top

R

Dabeeru C Rao, PHD, MS
Professor of Biostatistics (primary appointment)
Professor of Biostatistics in Genetics
Professor of Biostatistics in Psychiatry
Professor of Mathematics
Tenure Held At-Large in the Medical School
PHD Indian Statistical Institute 1971
BS Indian Statistical Institute 1967
MS Indian Statistical Institute 1968

Treva Kay Rice, MA, PHD
Professor of Biostatistics (primary appointment)
Professor of Psychiatry
BS University of Texas Arlington 1981
MA University of Colorado Boulder 1984
PHD University of Colorado Boulder 1987

Back to top

S

Kenneth B Schechtman, MS, PHD, MA
Professor of Biostatistics (primary appointment)
Professor of Medicine
Tenure Held At-Large in the Medical School
MS Purdue University 1971
PHD Washington Univ in St. Louis 1978
MA Washington Univ in St. Louis 1978
BS City University of New York 1967

Back to top

W

Guoqiao Wang, MS, MA, PHD
Assistant Professor of Biostatistics (primary appointment)
Assistant Professor of Neurology
MS Yunnan University 2007
MA University of Alabama-Tuscaloo 2010
PHD University of Alabama-Birmingh 2014

Back to top

X

Chengjie Xiong, PHD, MS
Professor of Biostatistics (primary appointment)
Professor of Mathematics
Professor of Neurology
BS Xinjiang University 1983
PHD Kansas State University 1997
MS Peking University 1989

Visit online course listings to view offerings for M21 MSB.


M21 MSB 503 Statistical Computing with SAS

Intensive hands-on summer training in SAS (Statistical Analysis System) during seven full weekdays. Students will learn how to use SAS for handling, managing, and analyzing data. Instruction is provided in the use of SAS programming language, procedures, macros, and SAS SQL. The course will include exercises using existing programs written by SAS experts. Contact the Program Managers for details, to register or to obtain permission of the Course Master (biostat-msibs@email.wustl.edu).

Credit 2 units.


View Sections

M21 MSB 506 Introduction to R for Data Science

This is an introduction to the R Statistical Environment for new users. R is "a freely available language and environment for statistical computing and graphics which provides a wide variety of statistical and graphical techniques: linear and nonlinear modeling, statistical tests, time series analysis, classification, clustering, etc." The goal is to give students a set of tools to perform statistical analysis in medicine, biology, or epidemiology. At the conclusion of this primer, students will: be able to manipulate and analyze data, write basic models, understand the R environment for using packages, and create standard or customized graphics. This primer assumes some knowledge of basic statistics as taught in a first-semester undergraduate or graduate sequence. Topics should include: probability, cross-tabulation, basic statistical summaries, and linear regression in either scalar or matrix form. Contact the program manager for details, to register, or to obtain permission from the course director.

Credit 2 units.


View Sections

M21 MSB 512 Ethics in Biostatistics and Data Science

This course prepares biostatisticians to analyze and address ethical and professional issues in the practice of biostatistics across the range of professional roles and responsibilities of a biostatistician. The primary goals are for biostatisticians to recognize complex situational dynamics and ethical issues in their work and to develop professional and ethical problem-solving skills. The course specifically examines ethical challenges related to research design, data collection, data management, ownership, security, and sharing, data analysis and interpretation, and data reporting and provides practical guidance on these issues. The course also examines fundamentals of the broader research environment in which biostatisticians work, including principles of ethics in human subjects and animal research, regulatory and compliance issues in biomedical research, publication and authorship, and collaboration in science. By the conclusion of the course, participants will understand the ethical and regulatory context of biomedical research; identify ethical issues, including situational dynamics that serve to foster or hinder research integrity, in the design and conduct of research and the management, analysis and reporting of data; and utilize strategies that facilitate ethical problem-solving and professionalism. Contact the program manager for details, to register, or to obtain permission of the course director (by email or phone: 314-362-1384).

Credit 2 units.


View Sections

M21 MSB 515 Fundamentals of Genetic Epidemiology

Lectures cover causes of phenotypic variation, familial resemblance and heritability, Hardy-Weinberg Equilibrium, ascertainment, study designs and basic concepts in genetic segregation, linkage and association.The computer laboratory portion is designed as hands-on practice of fundamental concepts. Students will gain practical experience with various genetics computer programs (e.g. SOLAR, MERLIN, QTDT, and PLINK). Auditors will not have access to the computer lab sessions. Prerequisite: R for Data Science (M21-506). Contact the Program Manager for details, to register, or to obtain permission from the Course Master (biostat-msibs@email.wustl.edu).

Credit 3 units.


View Sections

M21 MSB 5483 Human Genetic Analysis

Basic Genetic Concepts: meiosis, inheritance, Hardy-Weinberg equilibrium, linkage, segregation analysis; Linkage Analysis: definition, crossing over, map functions, phase, LOD scores, penetrance, phenocopies, liability classes, multipoint analysis, nonparametric analysis (sibpairs and pedigrees), quantitative trait analysis, determination of power for Mendelian and complex trait analysis; Linkage Disequilibrium Analyses: allelic association (case control designs and family bases studies), QQ and Manhattan plots, whole genome association analysis; population stratification; Quantitative Trait Analysis: measured genotypes and variance components. Hands-on computer lab experience doing parametric linkage analysis with the program LINKAGE, model free linkage analyses with GeneHunter and Merlin, power computations with SLINK, quantitative trait analyses with SOLAR, LD computations with Haploview and WGAViewer, and family-based and case-control association analyses with PLINK and SAS. The methods and exercises are coordinated with the lectures, and students are expected to understand underlying assumptions and limitations and the basic calculations performed by these computer programs. Auditors will not have access to the computer lab sessions. Prerequisite: M21-515 Fundamentals of Genetic Epidemiology. For details, to register, and to receive the required permission of the course director, contact the MSIBS program manager (by email or phone: 314-362-1384).
Same as L41 Biol 5483

Credit 3 units.


View Sections

M21 MSB 550 Introduction to Bioinformatics

Provide a broad exposure to the basic concepts, methodology and application of bioinformatics to solve biological problems. Specifically, the students will learn the basics of online genomic/protein databases and database mining tools, and acquire understanding of mathematical algorithms in genome sequence analysis (alignment analysis, gene finding/predicting), gene expression microarray (genechip) analysis, and of the impact of recent developments in the protein microarray technology. Prerequisite: R for Data Science (M21-506). Contact the Program Manager for details, to register, or to obtain permission from the Course Master (biostat-msibs@email.wustl.edu).

Credit 3 units.


View Sections

M21 MSB 560 Biostatistics I

This course is designed for students who want to develop a working knowledge of basic methods in biostatistics. The course is focused on biostatistical and epidemiological concepts and on practical hints and hands-on approaches to data analysis rather than on details of the theoretical methods. We will cover basic concepts in hypothesis testing, will introduce students to several of the most widely used probability distributions, and will discuss classical statistical methods that include t-tests, chi-square tests, regression analysis, and analysis of variance. Both in-class examples and homework assignments will involve extensive use of SAS. Prerequisite: M21-503, Statistical Computing with SAS®, or student must have good practical experience with SAS®. Students are required to participate in the "Computing/Unix" workshops offered free of charge prior to this course. For details, to register and/or to obtain the required permission of the Course Master, contact the Program Manager (biostat-msibs@email.wustl.edu or telephone 362-1384).

Credit 3 units.


View Sections

M21 MSB 570 Biostatistics II

This course is designed for students who have taken Biostatistics I or the equivalent and who want to extend their knowledge of biostatistical applications to more modern and more advanced methods. Biostatistical methods to be discussed include logistic and Poisson regression, survival analysis, Cox regression analysis, and several methods for analyzing longitudinal data. Students will be introduced to modern topics that include statistical genetics and bioinformatics. The course will also discuss clinical trial design, the practicalities of sample size and power computation and meta analysis, and will ask students to read journal articles with a view toward encouraging a critical reading of the medical literature. Both in-class examples and homework assignments will involve extensive use of SAS. Prerequisite: M21-560, Biostatistics I or its equivalent as judged by the course directors. For details, to register, and/or to obtain the required permission of the course director, contact the program manager (by email or phone: 314-362-1384).

Credit 3 units.


View Sections

M21 MSB 600 Mentored Research

Student undertakes supervised research in a mentor's lab. The goal is to acquire important research skills as well as good writing and presentation skills. The student finds a mentor and they together identify a research topic. A written thesis based on the research, prepared in the format of an actual scientific publication, must be submitted and presented to a select audience. The course masters will organize a few meetings throughout to facilitate the whole process. The course masters will determine the grade (pass/fail) in consultation with the mentors. Permission of the Course Masters is required.

Credit variable, maximum 6 units.


View Sections

M21 MSB 617 Study Design and Clinical Trials

The course will focus on statistical and epidemiological concepts of study design and clinical trials. Topics include: different phases of clinical trials, various types of medical studies (observational studies, retrospective studies, adaptive designs, and comparative effectiveness research), and power analysis. Study management and ethical issues are also addressed. Students will be expected to do homework and practice power analysis during lab sessions. Prerequisites: M21-560 Biostatistics I and M21-570 Biostatistics II. Permission of the course director required. For details, to register, and to receive the required permission of the course director, contact the program manager.

Credit 3 units.


View Sections

M21 MSB 618 Survival Analysis

This course will cover the basic applied and theoretical aspects of models to analyze time-to-event data. Basic concepts will be introduced including the hazard function, survival function, right censoring, and the Cox-proportional hazards (PH) model with fixed and time dependent covariates. Additional topics will include regression diagnostics for survival models, the stratified PH model, additive hazards regression models and multivariate survival models. Permission of the course director required. Prerequisites: M21-560 Biostatistics I and M21-570 Biostatistics II. For details, to register, and to receive permission from the course director, contact the program manager (by email or phone: 314-362-1384).

Credit 3 units.


View Sections

M21 MSB 621 Computational Statistical Genetics

This course is designed to give the students computational experience with the latest statistical genetics methods and concepts, so that they will be able to computationally implement the method(s)/model(s) developed as part of their thesis. Concentrating on the applications of genomics and computing, it deals with creating efficient new bioinfomatic tools to interface with some of the latest, most important genetic epidemiological analysis software, as well as how to derive, design and implement new statistical genetics models. The course also includes didactic instruction on haplotype estimation and modeling of relationship to phenotype, LD mapping, DNA pooling analysis methods, analysis approaches in pharmacogenomics (with an emphasis on possible genomic role in drug response heterogeneity), and epistasis (GxG) and GxE interactions; data mining methods, including clustering, recursive partitioning, boosting, and random forests; and fundamentals of meta-analysis, importance sampling, permutation tests and empirical p-values, as well as the design of monte-carlo simulation experiments. Prerequisite: Biostatistics I and II, permission of the instructor. Contact the Program Manager for the required permission of the Course Master (biostat-msibs@email.wustl.edu or 314-362-1384).

Credit 3 units.


View Sections

M21 MSB 630 Internship

The primary goal of the Internship program is for students to acquire critical professional experience so that they will be well prepared to enter the job market upon graduation. This provides an opportunity for students to develop contacts, build marketable skills and perceive likes and dislikes in the chosen field. Students will have an opportunity to work with experienced mentors (PIs) on a range of projects that may include data management, data analysis, study design, and protocol development among other things. Students may have opportunities to contribute to and participate in the preparation of publishable quality manuscripts. As part of the Internship requirements, each student will submit a one-page Abstract of the work performed as part of the internship and will give a presentation of the Internship experience. The grade (pass/fail) for each student will be determined in consultation with the mentor.

Credit variable, maximum 6 units.


View Sections

M21 MSB 660 Biomedical Data Mining

This course introduces methods and applications of biomedical data mining. Various computational and statistical methods will be presented, such as model selection and regularization, resampling methods, tree-based methods, and artificial intelligence. In addition to the common applications of the covered methods in biomedical sciences, this course will prepare students for future challenges and opportunities in data science. Prerequisites: M21 506, M21 560, M21 570, and M21 550. Matrix algebra is also highly recommended.

Credit 3 units.


View Sections

  • About Washington University
  • Programs of Study
  • Undergraduate
  • Graduate &​ Professional
    • Architecture &​ Urban Design
    • Art
    • Arts &​ Sciences
    • Business
    • Engineering
    • Law
    • Medicine
      • Mission &​ Vision
      • Areas of Study
        • Biostatistics
      • Degrees &​ Offerings
      • Academic Departments
      • People
      • Policies &​ Guidelines
      • Resources
      • Financial Information
    • Social Work &​ Public Health
    • Interdisciplinary Opportunities
    • University College
  • Prior Bulletins

Contact

One Brookings Drive
St. Louis, MO 63130
314-935-5000

Helpful Links

Admissions
Site Map
Student Financial Services
WebSTAC

Facebook Twitter Instagram

©2020-21 Washington University in St. Louis

Back to Top