Introduction
The future generation DNA sequencing developments, for instance the 1000 Genome schemes are already changing the face of DNA testing and collection of information relating to DNA testing. However, gigantic data groups created by both the government and the private sector need proper management and storage (McKenna et al, 104). A part from huge projects, genome sequencing at a particular research laboratory centers are also creating numerous sequencing data from various types of organisms especially human beings. The main objective of this essay is isolating the best social approach for the sake of balancing disadvantages and advantages of big data on DNA generated from the testing kits meant for genome testing, advantages of personal testing among other related issues.
Benefits of Personal Genome Testing
Genetic testing has prospective advantages, whether the outcomes are negative or positive. Test outcomes gives people a sense of reprieve from doubt and assist individuals make well-versed choices on the management of their personal well-being and upkeep. For instance, a negative test result may eliminate unnecessary hospital visits to the hospital for screening examinations (Gostin 111). On the other hand, a positive outcome implies one can go further and get medical attention on how to manage, monitor the medical progress, prevention, mechanisms, and treatment opportunities and some outcomes assist people make choices on whether they should have children or not.
Who Controls Large Databases Of Genetic Information?
Once a person gives his or her DNA information, other factors such as health and family health derives from the information. Due to technological advances, DNA sequencing and understanding became cheap (Bycroft et.al, 280). Whether the utilization of the genetic information is for scientific study, medical or other utilities, one thing should remain constant: a person’s privacy. There are numerous regulations and policies that aid in the protection of each person’s genetic information. There is an ongoing debate on whether more measures should be put in place in order to reinforce the already existing laws and policies.
While carrying out genomic studies, two aspects of scientific inquire need balancing sharing information widely for the sake of maximizing the ongoing research and at the same time the necessity to safeguard participants’ information from leaking out into the wrong hands. Attaining the right balance especially when it comes to genomic information gathered. Institutions such as National Health Institutes take manage genomic information generated from personal genetic testing (Bycroft et.al, 94). Therefore, an institution such as National Health Institutes controls accessibility to genetic information.
Social Approach
The best social approach when it comes to handling the ups and downs of genomic data is enactment of human rights regulations in all policies pertaining DNA testing. In addition, human rights encompass ethical issues, such as the right to control information. Each person has the right to remain anonymous and self-determine the use of DNA information (Ritchie et.al 278). Human rights dictate the morality, decisions, and mechanisms applied while handling peoples’ DNA information. Government all around the world need to consider the privacy and the right to securing information of its citizens. Aside from ethical issues, human rights encompass legal issues, which functions as policies and regulations meant to safeguard handling of DNA information.
In summary, due to the numerous people generating DNA information from DNA tool, there is a possibility of mishandling information hence the need to take human’s right approach since it contains numerous mechanism, which will in turn stop information mishandling.
Works cited
Bycroft, Clare, et al. "Genome-wide genetic data on~ 500,000 UK Biobank participants." BioRxiv (2017): 166298.
Gostin, Lawrence O. "Genetic privacy." Genetics and Gene Therapy. Routledge, 2017. 241-251.
McKenna, Aaron, et al. "The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data." Genome research 20.9 (2010): 1297-1303.
Ritchie, Marylyn D., et al. "Methods of integrating data to uncover genotype–phenotype interactions." Nature Reviews Genetics 16.2 (2015): 85.
