Microarray Gene Expression Analysis

Background

Gene expression profiling is a technique used in molecular biology to query the expression of thousands of genes simultaneously. While almost all cells cell in an organism contain the entire genome of the organism, only a small subset of those genes is expressed as messenger RNA (mRNA) at any given time, and their relative expression can be quantified using a variety of techniques, including cDNA microarrays where an arrayed series of microscopic spots of pre-defined DNA oligonucleotides known as probes are covalently attached to a solid surface.  Fluorescently labeled cDNA is prepared from an RNA sample and is hybridized to the complementary sequences on the microarray. The microarray is then scanned for the presence and strength of the fluorescent labels at each spot representing probe-target hybrids. The level of fluorescence at a particular spot provides quantitative information about the expression of the particular gene corresponding to the spotted cDNA sequence.  This information can then be used in a variety of bioinformatic tools and techniques to determine changes in expression between conditions and to identify genes significant to the specific conditions.

Analysis

Simbiot provides three sophisticated expression analysis function to analyze data from Affymetrix and Illumina cDNA microarrays.  Two functions are published Bioconductor (Gentleman, Carey et al. 2004) libraries: Limma (Smyth 2004) and LPE (Jain, Thatte et al. 2003), plus SAM (Tusher, Tibshirani et al. 2001) – one of the original expression analysis algorithms.  Simbiot’s implementation of SAM is based on the R version of the package.

Free demo accounts are available at http://www.simbiot.net.

Please also see more information about Simbiot Single User Accounts and Private Server installations as well as a brief introduction to microarray analysis.

References

Gentleman, R. C., V. J. Carey, et al. (2004). "Bioconductor: open software development for computational biology and bioinformatics." Genome Biol 5(10): R80.

Jain, N., J. Thatte, et al. (2003). "Local-pooled-error test for identifying differentially expressed genes with a small number of replicated microarrays." Bioinformatics 19(15): 1945-51.

Smyth, G. K. (2004). "Linear models and empirical bayes methods for assessing differential expression in microarray experiments." Stat Appl Genet Mol Biol 3: Article3.

Tusher, V. G., R. Tibshirani, et al. (2001). "Significance analysis of microarrays applied to the ionizing radiation response." Proc Natl Acad Sci U S A 98(9): 5116-21.