Time and place
12:30-2:00pm, 215 Dwinelle
Computer lab session
Please note room change.
Drop-in computer lab sessions
will be scheduled as needed on Fridays, 1-3pm, in 340A Haviland Hall
Office hours: TuTh 2:00-3:00pm, 109 Haviland Hall.
This course surveys statistical and computational
methods for the analysis of biomedical and genomic data, from the early
experiments to modern day genomic research.
Biological questions of interest include, but are not limited to:
modeling meiosis; genetic mapping; nucleotide and protein sequence
microarray data analysis; biological metadata analysis.
Related statistical topics include: numerical and graphical summaries
of data; stochastic processes (Markov processes, hidden Markov models,
Markov chain Monte Carlo); experimental design; loss-based estimation
(e.g., least-squares regression, classification, maximum likelihood
estimation, density estimation, variable/model selection); multiple
hypothesis testing; resampling (bootstrap, cross-validation);
The course also introduces statistical computing resources for the
analysis of biological data, with emphasis on the R language and
Bioconductor software packages (www.bioconductor.org).
In addition to discussing specific statistical and computational
methods, the course provides an introduction to basic notions in
genetics and molecular biology and involves the critical reading of
articles related to statistical analyses in the biological and medical
I encourage you to attend PH
296, the Statistics and Genomics Seminar (schedule
Health 240D, Section 001
Course control number: 76302
Online schedule of
STAT 200A and STAT 200B (may be taken concurrently)
Some familiarity with the S language (R or S-Plus).
Tutorials are available on the R
No formal training in biology is required; basic notions
presented in class and references will be provided for further reading.
and 50% final
Assignments will involve both theory and biological
data analysis using R.
The final project will consist of a written report and
presentation on a topic that involves the application of statistical
and computational methods to address a particular biological question.
I will provide a list of suggested topics.
There is no required textbook. Lecture
notes and references
will be provided on the class website.
I will use e-mail for important announcements. I have a list of e-mail
addresses from Bear Facts. If you are not on this list, please