Microarray Gene Expression data analysis

This course covers the analysis of gene expression microarray data using Affymetrix tools, R (Bioconductor) and Dchip Introduction: Gene expression can be studied through microarray experiments that interrogate genomewide transcripts to understand the underlying mechanisms of gene regulation in samples of interest. This course teaches researchers to perform analysis on Affymetrix data and transform a chip image to a list of genes that are up or down-regulated in an experiment. Various tools will be covered - Affymetrix Expression Console (replacing GCOS), Microsoft Excel, MathWorks MATLAB, and free tools like R/Bioconductor and dChip. It is geared towards researchers who conduct microarray experiments to study genome-wide expression changes and understand the underlying mechanisms of gene regulation in samples of interest. Why learn gene expression analysis? Most scientists are not able to analyze microarray data themselves and are not able to get desired results using traditional computer tools like Microsoft Excel or even with advanced software provided by commercial vendors. The freeware solutions come either with a steep learning curve or as black-box interfaces that provide limited functionality with little or no technical support. In the midst of all this is the fundamental lack of understanding among scientists on how the technology works and what the fundamental parts of the analysis are is striking. This course demystifies the analysis. Logistics: The course is divided into 8 sessions with pre-recorded videos, handouts, reference cards, examples, data, scripts and quizzes. Enrollees can contact the instructor with questions and get help on the projects. The main topics are listed below. Homework assignments will involve running commands learned in the live lectures. Introduction: No experience is required, although prior experience with any other programming language will be helpful. Math skills will also be useful. Price: $2400 for Commercial/Government enrollees and $1200 for Academic researchers and students. Syllabus: - - Expression Console for DAT->CEL->CHP. Quality metrics - - Creating and saving experiments, importing and exporting data, normalization settings - - Data transformation, filtering, hypothesis testing, differential expression analysis - - Dchip software - - R and Bioconductor - - Matlab and bioinformatics toolbox - - Clustering and classification for biomarker discovery - - Gene set, pathway and ontology enrichment analysis