Tutorial on Microarrays
(September 13-17, 2004)
Located in MBI Lecture Hall, Math Building, Room 240
Organizers: Sashwati
Roy and Chandan Sen
DNA microarrays are becoming a standard tool for
molecular biology research and clinical diagnostics by providing
a simple and natural means for surveying the genome in a very
systematic and comprehensive manner. Microarrays are miniature
arrays of gene fragments immobilized in a dense order on a solid
substrate. Because thousands or tens of thousands of gene fragments
can be present on a single microarray, data for entire genome
can be acquired in a single experiment. The power of DNA microarrays
lies in the ability to simultaneously score the hybridization
signals, which represent global gene expression patterns of biological
processes, and their dynamic variations. The tutorial will introduce
all key aspects of microarray technology, including definitions
of microarrays, types of microarray, array design, probe selection,
array fabrication, biological questions, experiment design, target
preparation as well as labeling, visualizing and analysis of microarray
images, and basic data analysis. The tutorial is meant for individuals
getting introduced to the microarray technology. The subject areas
include general principles underlying microarray printing, enzymatic
labeling, signal amplification, clustering methods and electronic
resources. The tutorial fosters an open and interactive format;
attendee questions and comments are encouraged.
Schedule
Monday - Friday, 9:00am - 12:00pm
Speakers: Chandan Sen and Sashwati Roy
Tutorial on Statistical Methods and Software for the Analysis
of Microarray Experiments (September 20-24, 2004)
Located in MBI Lecture Hall, Math Building, Room 240
Organizer: Nick
Jewell and Sandrine Dudoit
DNA microarray and other high-throughput genomic
experiments generate complex, high-dimensional datasets of multiple
types. Extracting meaningful and reliable biological information
from the analysis of these data presents new statistical and computational
challenges. This tutorial will discuss statistical design and
inference methods for microarray experiments. Topics to be covered
include: pre-processing (image analysis and normalization); multiple
testing procedures for the identification of differentially expressed
genes; hierarchical and partitioning cluster analysis; prediction;
and model selection. We will also consider the joint analysis
of microarray data with biological metadata such as Gene Ontology
(GO) annotation (www.geneontology.org).
The statistical methods to be discussed apply
to a broad range of problems beyond the analysis of microarray
data, such as the genetic mapping of complex traits using single
nucleotide polymorphisms (SNPs) and the identification of transcription
factor binding sites in ChiP-Chip experiments.
Computer lab sessions will allow participants
to explore statistical software resources for the analysis of
genomic data, with emphasis on R packages developed as part of
the Bioconductor Project (www.bioconductor.org).
Schedule
|
Monday 9/20
|
| 9:00-10:00am |
Sandrine Dudoit |
| 10:30-11:30am |
Sandrine Dudoit |
| 2:00-3:00pm |
Computer Lab |
|
Tuesday 9/21
|
| 9:00-10:00am |
Sandrine Dudoit |
| 10:30-11:30am |
Sandrine Dudoit |
| 2:00-3:00pm |
Computer Lab |
|
Wednesday 9/22
|
| 9:00-10:00am |
Nick Jewell |
| 10:30-11:30am |
Nick Jewell |
| 2:00-3:00pm |
Computer Lab |
|
Thursday 9/23
|
| 9:00-10:00am |
Nick Jewell |
| 10:30-11:30am |
Nick Jewell |
| 2:00-3:00pm |
Computer Lab |
|
Friday 9/24
|
| 9:00-10:00am |
Nick Jewell and Sandrine Dudoit |
| 10:30-11:30am |
Computer Lab |
