Microarray RNA transcriptional profiling: Part II. Analytical considerations and annotation

Abstract

This review summarizes the various data filtration, transformation and normalization processes for different array platforms (cDNA, oligos, one- and two-color), data analysis methods and their validation, and databases and annotation for RNA transcriptional profiling microarrays. This review is intended to introduce the beginner to the analyses and interpretation of gene expression studies using a nonmathematical approach for easier comprehension. Microarray analysis is not a trivial undertaking as there is no single method that works well for all, and results obtained from these analyses should be considered as a complement to other approaches.

Cutting the Gordian knot: taking a stab at corky root rot of tomato

“…It is therefore important to have fast and efficient assays to validate the biological importance of the genes/proteins identified (Ahmed 2006;Cristoni and Bernardi 2004).…”

Expression Microarray Proteomics and the Search for Cancer Biomarkers

“…The log ratios eliminate variability at each feature that affects both dyes to the same extent. However, Cy3 and Cy5 labeling differ in their action, resulting in what is termed intensity-dependent biases, in addition to a gene-specific dye effect [145]; b) the balancedblock design represents each individual array in a block. In case of two-class comparisons, this design would include samples from each of two classes to be compared that hybridize to every array in such a way that the classes are balanced with respect to dyes.…”

“…An obvious disadvantage of that approach is the doubling of arrays and resources. The reference design is also less efficient than the other designs because more information is collected from the reference group than each of the classes in spite the reference group is not the main group of interest [2,145,147].…”

“…For class comparison studies, which compare two or more classes (e.g., tumor versus normal) with respect to expression, the balanced-block design is preferred, whereas the loop design may be preferred for class discovery studies, which seeks to find new groups within a predefined class [145,147]. Therefore, the choice of an experimental design is not clear cut and largely depends on the objectives of the study.…”

“…Biological replication ensures that results can be generalized to the population from which samples were taken. If biological replication is replaced by technical replication, the results apply only to the samples at hand [2,145,147]. Therefore, the experimenter must seek to have samples replicated biologically rather than technically for microarray measurements.…”