Genomics and Genetic Data: A Third Eye for Doctors

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In the recent decade, data have received attention from sectors, organizations, and industries. Numerous data are generated by many smart devices or machines (through communication). Genomic data, genetic data are examples of these data or Big Data. In general, Genetics and Genomics play a vital role in healthcare sector. It should be noted that Genetics and Genomics sounds similar, but they are not, that is, genetics is considered as a subset of genomics. Genetics deals with the study of single gene whereas genomics is the study of group of genes (which is known as genome) and their interrelationship. Genetics is concerned about how the genetic traits are transmitted. Genetics is a familiar term, but genomic is a new field which has become popular in the last few decades due to the advancement in the field of 396computational biology. The reduction in DNA sequencing cost has increased the usage of genomic data which can help to explore useful information regarding human life. The advancement in genetics or genomics field leads to a transition from traditional medicine to personalized medicine. Apart from the accidental death, genomic factors play an important role in the causes of human death. A better study of genomic data helps the human being to prevent some chronic diseases (like cancer, HIV, etc.) and hence to improve the health of patients and can help to healthcare sector to receive more useful innovations. Currently, many existing tools are available to extract relevant information from genomic data, also to preserve useful/sensitive or genomic privacy. Use of genomic data in research or other clinical purposes may cause leakage of information, which is a serious issue. So it is necessary to find some efficient techniques to overcome such raised challenges or issues. Hence, many researchers tried to provide efficient mechanism, but failed to protect due to various reasons like different preferences of users. Hence, in this article, we give insight to various topics, such as importance of genomic data, genetic analytics, existing tools, limitations, and raised issues, challenges (including identified research gaps) in analyzing this genomic data, or preserving user’ information, etc.