Answer to Question #154932 in Bioinformatics for vaibhav

Question

(a) Why do you have to normalize microarray data to compare two conditions? Explain two normalization techniques that can be used here.

(b) Describe and discuss specific problems likely to appear on a microarray? Describe and discuss what measures can be taken to reduce or eliminate such effects from a data analysis point of view?

Answer 1

a. The comparison of microarray is based on the variability measures derived from the replicated microarray samples. Normalization becomes a standard process for removing some of the variations which affect the measured gene expression levels. Two-channel (color) microarrays are usually normalized with LOESS, but one-channel arrays usually only with a between-array method (like quantile). 

b. The most significant problems of microarrays include the high cost of a single experiment, the large number of probe designs based on sequences of low-specificity, as well as the lack of control over the pool of analyzed transcripts.

The problem can be solved by reducing the cost of the equipment by designing something which gives specific results with reduced costs