NGS Short Read Alignment Algorithms and the Role of Big Data and Cloud Computing
Rexie J A M1, Kumudha Raimond2, Mythily M3, Kethsy Prabavathy A4

1Rexie J A M, Computer Science and Engineering, Karunya Institute of Technology and Sciences, Coimbatore, India.
2Kumudha Raimond, Computer Science and Engineering, Karunya Institute of Technology and Sciences, Coimbatore, India.
3Mythily M, Computer Science and Engineering, Karunya Institute of Technology and Sciences, Coimbatore, India.
4Kethsy Prabavathy, Computer Science and Engineering, Karunya Institute of Technology and Sciences, Coimbatore, India.

Manuscript received on 25 June 2019 | Revised Manuscript received on 05 July 2019 | Manuscript published on 30 July 2019 | PP: 967-971 | Volume-8 Issue-9, July 2019 | Retrieval Number: I8001078919/19©BEIESP | DOI: 10.35940/ijitee.I8001.078919

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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: Next Generation Sequencing (NGS) raises opportunities to the computational field for fast and accurate methods for the various challenges associated with NGS data. NGS technology generates a large set of short reads of size 50 to 400 base pairs as a result of biological experiments done on the samples taken from species. Such raw reads are not directly ready for doing most of the analysis or comparative studies to figure out medical related solutions. Hence, the reads have to be assembled to form a complete genome sequence. During the assembly process, there is a high chance of erroneous positioning. Some strategy has to be applied to correct such errors. Once the error-free sequence data is prepared, it is ready for further analysis. The analysis may assist in identifying disease and its cause, similarity check, genetic issue, etc. All of these processes involve data of huge size (in terms of millions per day). To improve the performance of the algorithms working on such vast amount of data, the latest technologies such as Big Data and Cloud Computing can be incorporated. Here, in this paper the evolution of the algorithms for NGS data alignment and the role of Big Data and Cloud Computing technologies are discussed.
Index Terms: NGS Short Read Alignment, Burrows Wheeler Transform, Suffix Array, Big Data, Cloud Computing.

Scope of the Article: Cloud Computing.