4 - Central Institute of Brackishwater Aquaculture

National Workshop-cum-Training on Bioinformaticr and Information Management in Aquaculture
(Y TAT
2-
Cu~rljrnnent
0 P
I '-
0
-
z
P
1 -
W C
1 0-
.2 0
Principal Component I
Fig. 3 An example of Principal Component Analysis generated by SPSS
3. MICROARRAY ANALYSIS
Microarray provides insight into the transcriptional state of the cell, measuring
RNA levels for thousands of genes at once. It requires preparation of mRNA from
cells growing under certain experimental conditions. Subsequently, the labeled
cDNA mixture is hybridized to the microarray. After detection of the signals,
image analysis programs are used to determine spot intensities. Data produced
may be regarded as a table, each row representing a gene, each column
standing for an experimental condition. Multiple measurements for each
condition, involving repeated sampling, labeling, and hybridization, offer the
opportunity of extracting more robust signals. The columns of the table have to
undergo a normalization procedure, correcting for affine-linear transformation
among the columns. all of the methods recently used for microarray data
analysis would result in an outline of applied statistics, however. Most methods
fall into one of three groups, namely clustering, classification, and projection
methods. Examples of clustering techniques are k-means clustering, hierarchical
clustering, and self-organizing maps. Classification methods take as input a
grouping of objects and aim at delineating characteristic features common and
discriminative to the objects in the groups. Examples of classification methods
range from linear discriminant analysis to support vector machines or
classification and regression trees.
3.1. Generation of Microarray Images
There are a variety of microarray platforms that have been developed to
accomplish and the basic idea for each is a glass slide or membrane that is
spotted or "arrayed" with DNA fragmehts or oligonucleotides that represent
specific gene coding regions. Purified RNA is then fluorescently- or radioactively
labeled and hybridized to the slidelmembrane. In some cases, hybridization is
done simultaneously with reference RNA to facilitate comparison of data across
multiple experiments. After thorough washing, the raw data is obtained by laser
scanning or autoradiographic imaging. The final step of the laboratory process is
to produce an image of the surface of the hybridized array. Fluorescently labeled
microarrays can then be "read" with commercially available scanners scanning
confocal microscopes with lasers exciting at wavelengths specifically for Cy3 and