800-618-4681 | Request Info
Mobile Menu

RBIF 114

Whole Genome Expression Analysis and Biomarker Discovery

Microarrays are routinely used in genomic studies to detect changes in mRNA expression levels. These experiments have fundamental statistical and data processing challenges associated with them. This course covers: the statistical aspects of experimental design, biological and technical replicates, preprocessing, quality assessment, parametric and non-parametric statistical tests, multiple-hypothesis testing, P-value correction and false discovery rates, visualization techniques (e.g. heatmaps, volcano plots), and biological significance (e.g. functional annotation, pathways, hypergeometric tests, gene set enrichment).

At the end of the course, students will be able to:

Design, normalize and analyze single- and dual-channel microarray experiments from several platforms including Affymetrix and Agilent.

Gain a working experience for methods of analysis of microarray experiments, from the most basic preprocessing analysis to advanced machine learning, identifying genes or chromosomal regions of interests, and annotation of large genomic data.

Choose methods of analysis for various types of data.

Attend an Online Open House

Please join us for our next Online Open House. Check out our Admissions Events to see a listing of upcoming program-specific Online Open Houses, and get connected with program chairs, current students and administrative staff at GPS.

Get Advice

Brandeis GPS is committed to giving you the support you need to succeed. From the moment you begin the application process to the day you graduate and beyond, our advising team is here to support you. Talk to an enrollment advisor today.

Explore Online Learning

Our unique approach to online learning is designed by and for working professionals. Learn more about the tools and skillsets you'll develop through our master's programs.