Tandem repeat interval pattern identifies animal taxa

Author:

Bhattacharyya Balaram1ORCID,Mitra Uddalak1ORCID,Bhattacharyya Ramkishore2

Affiliation:

1. Department of Computer and System Sciences, Visva-Bharati University, Santiniketan 731235, West Bengal, India

2. Saas, Oracle America Inc., Bellevue, WA 98004, USA

Abstract

Abstract Motivation We discover that maximality of information content among intervals of Tandem Repeats (TRs) in animal genome segregates over taxa such that taxa identification becomes swift and accurate. Successive TRs of a motif occur at intervals over the sequence, forming a trail of TRs of the motif across the genome. We present a method, Tandem Repeat Information Mining (TRIM), that mines 4k number of TR trails of all k length motifs from a whole genome sequence and extracts the information content within intervals of the trails. TRIM vector formed from the ordered set of interval entropies becomes instrumental for genome segregation. Results Reconstruction of correct phylogeny for animals from whole genome sequences proves precision of TRIM. Identification of animal taxa by TRIM vector upon feature selection is the most significant achievement. These suggest Tandem Repeat Interval Pattern (TRIP) is a taxa-specific constitutional characteristic in animal genome. Availabilityand implementation Source and executable code of TRIM along with usage manual are made available at https://github.com/BB-BiG/TRIM. Supplementary information Supplementary data are available at Bioinformatics online.

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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