Microarray Data Analysis

Microarrays have found wide use in drug discovery and development, diagnostics, pharmacogenomics, toxicology, forensics, cladistics, bio defence, biomarker discovery and development, and gene/disease association studies. Analysis of the data produced by microarrays is thus of great importance. In this course, students are taken through an intensive, hands-on training on creating microarrays and analyzing and interpreting microarray data.

The training includes introduction to the R programming language and the use of various Bioconductor packages to load raw intensity files, analyze the files, retrieve sample annotation, assess data quality using images, box plots, and quality measures, normalize the data, and identify differentially expressed (DE) genes for 2-group and multiple arrays. Students are also introduced to NCBI’s Gene Expression Omnibus (GEO) and EMBL’s ArrayExpress. Normalization tools covered include the multi-array average (RMA) algorithm, MAS 5.0, Plier, dChip, and GCRMA.       Continue Reading »