Version 1
: Received: 4 December 2019 / Approved: 5 December 2019 / Online: 5 December 2019 (11:36:25 CET)
How to cite:
Abdullahi, K.B. Application of Statistical Mirroring in Biological Sequence Analysis. Preprints2019, 2019120069. https://doi.org/10.20944/preprints201912.0069.v1
Abdullahi, K.B. Application of Statistical Mirroring in Biological Sequence Analysis. Preprints 2019, 2019120069. https://doi.org/10.20944/preprints201912.0069.v1
Abdullahi, K.B. Application of Statistical Mirroring in Biological Sequence Analysis. Preprints2019, 2019120069. https://doi.org/10.20944/preprints201912.0069.v1
APA Style
Abdullahi, K.B. (2019). Application of Statistical Mirroring in Biological Sequence Analysis. Preprints. https://doi.org/10.20944/preprints201912.0069.v1
Chicago/Turabian Style
Abdullahi, K.B. 2019 "Application of Statistical Mirroring in Biological Sequence Analysis" Preprints. https://doi.org/10.20944/preprints201912.0069.v1
Abstract
Sequence alignment and comparison through pairwise, multiple, global and local techniques are the main principles that underpin comparative genomics. However, most of the algorithms used are alignment-based which imposed some limitations on their use and application. In an attempt to provide an alignment-free alternative approaches, a methodology of comparative optinalysis and statistical mirroring was used and adopted to provide a suitable alternative for multiple genomic sequence comparison. In this article, methods comparison with MUSCLE, MUFFT, Clustal Omega, and T-Coffee was designed to assess the suitability and statistical power of statistical mirroring as an alternative method for multiple genomic sequences comparison using different sets of logically generated biological sequence datasets with different problems and computational complications. The results of the comparisons validate that statistical mirroring is a suitable alignment-free alternative approach for multiple genomic sequence comparison. The applied method (statistical mirroring) distinguishes itself over MUSCLE, MUFFT, Clustal Omega, and T-Coffee in specificity to a position-specific changes, specificity to a base-specific changes, cladogram and phylogenetic linearity, alignment independency, computational simplicity, and limit of input capacity.
Computer Science and Mathematics, Computational Mathematics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
