Analysis of genomic sequences by Chaos Game Representation

Abstract

The distribution of positions in the CGR plane were shown to be a generalization of Markov chain probability tables that accommodates non-integer orders. Therefore, Markov models are particular cases of CGR models rather than the reverse, as currently accepted. In addition, the CGR generalization has both practical (computational efficiency) and fundamental (scale independence) advantages. These results are illustrated by using Escherichia coli K-12 as a test data-set, in particular, the genes thrA, thrB and thrC of the threonine operon.

Similarity analysis for DNA sequences based on chaos game representation. Case study: The albumin

“…Each CGR image is described by a numerical matrix generated using the versatile tool CGREx presented by Achuthsankar et al in 2009. Analysis based on this type of associated matrices considered as generalized scaleindependent Markov probability tables was previously used in the development of new statistical analysis for DNA sequences (Almeida et al, 2001).…”

Spectral Analysis of Global Behaviour of C. Elegans Chromosomes

“…The third technique is submerged from the Chaos Game Representation (CGR) images which can forms a global signature of bio-sequences (Almeida et al, 2001;Cenac et al, 2004;Deshavanne et al, 1999Deshavanne et al, , 2000Joseph & Sasikumar, 2006;Oliver et al 1993;Fiser et al, 1994). The CGR paradigm is a holistic way of DNA representation.…”

“…Second, the first point is plotted halfway between the center of the square, and the corner corresponding to the first nucleotide of the sequence. Third, the new point are marked successively half way between the previous point and the corner corresponding to the base of each nucleotide read from the sequence (Almeida et al, 2001;Joseph 2006). A generated CGR image can be viewed as an image of distributed dots.…”

“…The clustering dots in the lower corners indicate a slightly high concentration in A and T. It is known that CGR patterns depict base composition. In fact, we divide the CGR space with a grid of size k (i.e (2 k × 2 k ) pixels) and we count occurrence in each quadrant, the frequency of k-lengthen words occurrence can be estimated and the frequency matrix then extracted is called FCGR (Frequency Chaos Game Representation) (Almeida et al, 2001;Deshavanne et al, 2000;Jeffrey, 1990). …”

ANN based Genome Classifier using Frequency Chaos Game Representation

“…Director, Centre for Bioinformatics, University of Kerala, Thiruvananthapuram, Kerala, INDIA (sankar.achuth@gmail.com) CGR space with a grid of appropriate size and counting the occurrences in each quadrant. These frequency matrices obtained from CGR are termed as FCGR [3]. In this paper, 8X8 FCGR is used for representing each DNA data.…”