Application of Principal Component Analysis for Gene Sequences (cDNA microarrays)

Abstract

In this study, principal component analysis has been applied on data comprising of 6675 gene and 20 sequence collected by using cDNA microarray technology from livers of mice used in toxicology studies in certain time periods. Forming of gene groups from similar expression profiles and description of related genes which are implemented by similar component loads among the groups have been explained by using this cDNA technology. Besides that, interpretation and decomposition of factors (components) from correlation matrix which belongs to same data group have been explained. Some of the methods developed for minimizing the data set to fewer components which can explain the whole data structure have been evaluated. According to methods, if we assume that the first 9 eigen values are enough to describe the whole variance, then in this case, it is thought that it is good enough to describe the whole variance by using 9 eigen values with a variance loss of 20,79% instead of describing the whole variance by using 20 eigen values.