Next Generation Sequencing in Big Data
A huge revolution has taken place in the area of Genomic science. Sequencing of millions of DNA strands in parallel and also getting a higher throughput reduces the need to implement fragment cloning methods, where extra copies of genes are produced. The methodology of sequencing a large number of DNA strands in parallel is known as Next Generation Sequencing technique. An overview of how different sequencing methods work is described. Selection of two sequencing methods, Sanger Sequencing method and Next generation sequencing method and analysis of the parameters used in both these techniques. A Comparative study of these two methods is carried out accordingly. An overview of when to use Sanger sequencing and when to use Next generation sequencing is described. Increase in the amount of genomic data has given rise to challenges like sharing, integrating and analyzing the genetic data. Therefore, application of one of the big data techniques known as Map Reduce model is used to sequence the genetic data. A flow chart of how genetic is processed using MapReduce model is also present. Next Generation Sequencing for analysis of huge amount of genetic data is very useful but it has few limitations such as scaling and efficiency. Fortunately recent researches have proven that these demerits of Next Generation Sequencing can be easily overcome by implementing big data methodologies.
Next Generation Sequencing, DNA Strands, Bi data analytics, MapReduce model, Sanger Sequencing
Chinmayee C | Amrita Nischal | C R Manjunath | Soumya K N