Statistical Genetics

Statistical Genetics at UCLA

Statistical genetics is concerned with the analysis of genetic data. Due to rapid progress in laboratory techniques, there is an ever-increasing slew of new data: the 3rd generation of genetic markers (SNPs), the DNA sequence of numerous organisms, gene-statement information (transcriptional profiling), and an increasing amount of knowledge about gene function. Statisticians play an important role in the analysis and the design of genetic studies.

Statistical genetics overlaps with fields such as biomathematics, bioinformatics, biology, epidemiology, genetics, etc. People in the department have worked and are working on methods in linkage analysis, allelic association tests, gene statement array data analysis, sequence analysis, comparative genomics, phylogenetic tree reconstruction, etc.


In the department of Biostatistics, many of the faculty have been involved in statistical genetics:

  • Tom Belin
  • David Elashoff
  • David Gjertson
  • Steve Horvath
  • Christina Ramirez
  • Janet Sinsheimer
  • Rob Weiss

There are also many people in other departments who develop methods for analysis of genetic data, or work on problems relating to statistical genetics.

  • Rita Cantor (Human Genetics)
  • Nelson Freimer (Neuropsychiatric Institute)
  • Darlene Goldstein (Statistics)
  • James A. Lake (Biology)
  • Ken Lange (Biomathematics, Human Genetics)
  • Ker-Chau Li (Statistics)
  • Jeanette Papp (Human Genetics)
  • Christina Palmer (Neuropsychiatric Institute)
  • Susan Smalley (Neuropsychiatric Institute)
  • Eric Sobel (Human Genetics)
  • Arthur Woodward (Psychiatry)

Below we list a link to the Bioinformatics program at UCLA. Please inform us if you know someone who should be added to this list.


UCLA offers several courses that are interesting and relevant for students interested in statistical genetics. As examples (see the corresponding departmental websites for more information):


  • 237 A - Theoretical genetic modeling
  • 237 B - Applied genetic modeling


  • 202 - Fourier Analysis in Biology
  • 203 - Stochastic Methods in Biology


  • 202 - Bioinformatics Interdisciplinary Research Seminar
  • 260 - Bioinformatics and Genomics

Human Genetics

  • 236 - Advanced Human Genetics

Molecular, Cell, and Developmental Biology

  • 248 - Molecular Genetics
  • 253 - Macromolecular Structure
  • 222A - Molecular Evolution


  • 216 - High dimensional data analysis



  • Mathematical and Statistical Methods for Genetic Analysis, Kenneth Lange Springer-Verlag, New York, 1997.
  • Analysis of Human Genetic Linkage, 3rd Ed, Jurg Ott Johns Hopkins University Press, Baltimore, 1999.