2017 IEEE International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET 2017)

276 / 2017-01-31 16:43:14

Genome Sequencing using MapReduce and Hadoop – A Technical Review

5881,7212,12688,12689

The technique that allows for researchers to read and convert the genetic information found in the DNA of any organisms is called Genome Sequencing. Genome Sequencing involves determining the order of the nucleotide sub units found in DNA, which consists of a small number of bases called short reads. The human genome is approximately 3 billion bases in length, which would take months or years to be processed on a single machine. So large numbers of short reads are available in such sequencing. In these cases, the first step in the data analysis pipeline is the short read mapping problem. Speed is becoming significantly important and challenging due to the huge volume of data. In this paper, we have proposed an architecture that will take a dataset of DNA sequencing as an input and split them across the cluster machine by applying Map Reduce implementation of hadoop to make the search efficient for large scale genome sequencing applications.