Statistical Genetics

Director: Prakash Gorroochurn, PhD

The Statistical Genetics Track of the MS degree program (MS/SG) trains students in the skills critical to the design and analysis of genetic data from human studies, touching upon clinical aspects, laboratory issues, and modern statistical analyses. Students take courses in human and population genetics, biostatistics, epidemiology, statistical genetics, and computational modeling. The program also emphasizes training in research communication skills to facilitate effective collaborations with scientists in other disciplines necessary in the rapidly changing field of genetics.

The MS/SG Track is intended for individuals who plan careers, or are actively engaged, in genetic research. Applicants to the track must, therefore, demonstrate an interest in genetics as well as a facility for quantitative reasoning.

The MS/SG may serve as a stand-alone degree or can be earned by graduate students who plan to pursue a doctorate at Columbia University or elsewhere. The track consists of 36 academic credits in addition to required capstone experience. The program usually requires at least three semesters of full-time study, and the typical time to completion is two years. If preferred, candidates may pursue the MS/SG degree on a part-time basis, but must complete the program within five years of the start date.

“This is a very exciting time to be involved with statistical genetics as recent, and certainly future, discoveries will clearly continue to have a profound effect in public health and medicine.”

Prakash Gorroochurn, PhD
Associate Professor of Clinical Biostatistics


The MS in Biostatistics Statistical Genetics Track is intended to provide students with the skills to design and analyze research using genetic data from human studies. Competencies of the Statistical Genetics Track are achieved through a curriculum of  at least 36 credit hours of course work and the capstone experience.

In addition to achieving the MS in Biostatistics core competencies, students in the Statistical Genetics Track gain the following specific competencies in the areas of data analysis and computing, public health and collaborative research, teaching statistical genetics, and statistical genetics research.

Upon satisfactory completion of the MS in Biostatistics Statistical Genetics Track, graduates will be able to:

Data Analysis and Computing

  • Use genetic analysis programs and interpret the results

Public Health and Collaborative Research

  • Formulate testable hypotheses in human genetics and design studies to test those hypotheses

  • Understand and explain the factors that go into selecting appropriate samples

  • Understand and explain the critical importance of phenotype definition

Teaching Statistical Genetics

  • Explain the mathematical underpinnings of genetic analysis, including familial aggregation studies, twin studies, and segregation, linkage, and association analysis

  • Explain the biological underpinnings of genetic influences on disease risk

Statistical Genetics Research

  • Test and evaluate new methods of genetic analysis as they become available

  • Demonstrate familiarity with the role of laboratory techniques such as genotyping and sequencing, extracting DNA from blood, PCR; and

  • Demonstrate knowledge of the role of microarray technology and other current molecular-biological techniques.

Course Requirements

The MS in Statistical Genetics curriculum is designed to achieve the program’s competencies through courses totaling 36 credit hours and the capstone experience. The curriculum includes 30 credits of required course work and 6 credits of electives.

The required courses will enable degree candidates to gain proficiency in genetic study design and analysis. In rare circumstances, one or two required courses may be waived for students with demonstrated expertise in that field of study; however, students must still complete a minimum of 30 credits in order to be awarded the MS/SG degree. If a student places out of one or more required courses, s/he may instead opt to take a more advanced course in the same area or another elective course in Biostatistics or other discipline with the approval of the student’s faculty advisor.

Students wishing to waive one or more courses must request approval in writing from their advisors and the Director of Academic Programs.

Required Courses

The required courses enable degree candidates to gain proficiency in genetic study design and analysis.

Course #

Course Name



Principles of Epidemiology






Statistical Inference



Advanced Statistical and Computational Methods



Analysis of Categorical Data



Statistical Genetic Modeling



Biostatistical Methods I



Biostatistical Methods II



Statistical Population Genetics



Statistical Methods in Genetic Epidemiology Journal Club



Capstone Consulting Seminar



Students also select 2+ courses from the list below. Other advanced courses from the Department of Biostatistics, other Departments in the Mailman School of Public Health, or elsewhere at Columbia may be substituted with approval of the student's academic advisor.

Course #

Course Name


P6385Principles of Genetics and the Environment I
P6386Principles of Genetics and the Environment II
P6700Selected Issues in Sociomedical Sciences
P8117Nonparametric Statistics
P8157Analysis of Longitudinal Data
P8160Topics in Advanced Statistical Computing
P9154Discrete Statistical Analysis
P8307Molecular Epidemiology
P8405Genetics in Epidemiology
P8414Cancer Epidemiology
P8419Neurobiology and Genetics of Psychiatric Disorders
P8422Perinatal Epidemiology
P8440Epidemiology of Cardiovascular Diseases
G4055Decision Support in Biomedicine
G4060Evaluation Methods in Biomedical Informatics
W4606Elementary Stochastic Processes (Morningside campus)


Sample Timeline

Below is a sample timeline for MS/SG candidates. Note that course schedules change from year to year, so that class days/times in future years will differ from the sample schedule below; you must check the current course schedule for each year on the course directory page.

Fall ISpring IFall IISpring II
P8130-Biostatistical Methods IP8131-Biostatistical Methods IIP8149-Statistical Population GeneticsP8139-Statistical Genetics Modeling
P8104-ProbabilityP8109-Statistical InferenceElectiveP8163-Statistical Genetics Journal Club
P6400-Principles of EpidemiologyP8119-Advanced Statistical & Computational MethodsElectiveP8185-Capstone Consulting Seminar
 ElectiveElectiveCompletion of practicum requirements


Practictum Requirement

One term of practical experience is required of all students, providing educational opportunities that are different from and supplementary to the more academic aspects of the program. The practicum may be fulfilled during the school year or over the summer. Arrangements are made on an individual basis in consultation with faculty advisors who must approve both the proposed practicum project prior to its initiation, and the report submitted at the conclusion of the practicum experience. Students will be required to make a poster presentation at the department’s Annual Practicum Poster Symposium which is held in early May.

Capstone Experience

P8185: Capstone Consulting Seminar

A formal, culminating experience for the MS degree is required for graduation. The capstone consulting seminar is designed to enable students to demonstrate their ability to integrate their academic studies with the role of biostatistical consultant/collaborator, which will comprise the major portion of their future professional practice.  

As part of the seminar, students are required to attend several sessions of the Biostatistics Consulting Service (BCS). The Consultation Service offers advice on data analysis and appropriate methods of data presentation for publications, and provides design recommendations for public health and clinical research, including preparation of grant proposals. Biostatistics faculty and research staff members conduct all consultation sessions with students observing, modeling, and participating in the consultations.

In the capstone seminar, students present their experience and the statistical issues that emerged in their consultations, developing statistical report writing and presentation skills essential to their professional practice in biomedical and public health research projects.

P8163: Statistical Methods in Genetic Epidemiology Journal Club

This monthly Journal Club exposes students to current papers in genetic analysis. Additionally, each student must present at least one paper at the Journal Club over the course of his/her time in the program.



Justine Herrera, MA
Director of Academic Programs
Department of Biostatistics
Columbia University
jh2477 [at]
(212) 342-3417


More information on Admission Requirements.