BIOS 567: Statistical Methods for High-throughput Genomic Data I
Course Time
Monday, Wednesday 12:00PM – 1:20PM
Room
One Capital Square, 5-009
Office hours
Monday, Wednesday 1:30PM– 2:30PM
Office
One Capital Square, 7018
Course Objectives
During this course students will gain insight regarding the technology underlying
custom spotted and oligonucleotude microarrays, image analysis, normalization,
and expression summary methods; students will learn how to apply supervised
and unsupervised learning methods to microarray data. At the conclusion of
the course students will be able to read raw microarray data into the R
programming environment and perform all preprocessing and analytical procedures
presented.
Bioinformatics
Bioinformatics is interdisciplinary, requiring a knowledge base in biology,
computer science, and statistics. The operational definition of 'bioinformatics'
for this course is "The application of information technology and statistical
methods to the study of biological problems." The biological problems
on which we will focus are gene expression studies conducted using microarray
technology. Due to the nature of these large datasets, students will learn
some basic programming skills in R.
Required Text
Sorin Draghici (2012) Statistics and Data Analysis for Microarrays Using R and Bioconductor. Chapman & Hall/CRC, Boca Raton, Florida.