Metagenomic Classification using Centrifuge
Tanaya Jadhav1, Meghana Nagori2
1Tanaya Jadhav, ME Student in Department of Computer Science and Engineering, Government College of Engineering Aurangabad.
2Meghana Nagori, Lecturer / Associate Professor / Data Science.
Manuscript received on 10 March 2019 | Revised Manuscript received on 18 March 2019 | Manuscript published on 30 July 2019 | PP: 6004-6007 | Volume-8 Issue-2, July 2019 | Retrieval Number: B3725078219/19©BEIESP | DOI: 10.35940/ijrte.B3725.078219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: To assess the quality of food is a major challenge the food industry faces today. It is of utmost importance to test it for contaminates and non-edible material that may be present. To overcome these challenges metagenomic classification is majorly useful. Several researches involve various classification techniques and their studies. Difficulties in metagenomic classification include increasing number of genomes thereby requirement of computational methods to have high speed as well as high accuracy so as to compare DNA sequences to genomes. Centrifuge is a classification tool for quantification of species present in a sample so as to monitor the quality of the same. Given a food sample Centrifuge effectively classifies the species present in it enabling a timely and accurate analysis.
Index Terms: Burrows-Wheeler Transform, Centrifuge, FM index, Metagenomics, Metagenomic Classification.
Scope of the Article: Classification