STATISTICS OF MICROARRAY
AND RELATED BIOLOGICAL DATA
June 21 - 26, 2005

Instructors:
Vincent Carey, Harvard University
Mark Reimers, National Cancer Institute
Javier Cabrera, Rutgers University

High-throughput biology, epitomized by the rapid growth in numbers of DNA microarray-based experiments, is rapidly generating enormous observation sets. Biologists seeking to make sense of this growing body of data need to have a firm grasp of statistical methodology. This course is designed to build competence in statistical and related quantitative methods for the analysis of high-throughput biological and biochemical data, from which meaningful inferences about biological processes can be drawn.

This short residential course is being offered primarily as a supplement to the 2005 course on DNA Microarray Applications though prospective applicants may apply to attend this course separately. The course will begin in the late afternoon of Tuesday June 21, 2005, and end with a special dinner on Saturday June 25, with departure on the morning of June 26.

Topics in the 2005 short course will include:
R mini-tutorial
Bioconductor
Review of multivariate statistics
Discrimination and Classification
Expression arrays - experimental design, array design, quality control, normalization and probe-level analysis for spotted arrays and for Affymetrix(TM) chips, exploratory analysis and tests of significance
Discrimination and Classification
Leveraging Annotations (eg. Gene Ontology)


Preference will be given to students accepted into the 2005 course on DNA Microarray Applications but we also hope to attract biologists who have already demonstrated a strong interest or background in quantitative thinking and are comfortable with some aspects of programming. We are also interested in attracting applicants from mathematics, physics and related disciplines who already have a firm grasp of major biological concepts and are interested in focusing their efforts on large biological datasets such as whole genome or expression microarray data.

Applicants should send resume and brief outline of their area of research and reasons for taking the course to the Course Registrar by April 15 latest. Also state if you are interested in bringing your own datasets for possible analysis during the course.

In future years (2006 and beyond), we hope to amalgate data analysis aspects of the existing courses into a single ten-day course that would address the application of statistical and related quantitative methods to large biological datasets (and meta-datasets) produced from expression arrays, whole genome arrays, CHIP-chip and related laboratory experiments. The course will train participants in how rigorous statistical and quantitative concepts are equally important in the experimental design phase as in the data analysis phase of any research project involving the generation of large datasets.

This course is supported with funds provided by the National Cancer Institute