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Genetic Variance Study in Human on the Basis of Skin/Eye/Hair Pigmentation Using Apache Spark

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1087))

Abstract

Heredity and variation are the basis of genetics. Human beings show variation on the basis of skin/hair/eye color. The diversity in the phenotypes is originated due to variations at the genetic level. It has been observed that specific populations across the globe share similar shades of color. It has been reported that pigment melanin is responsible for skin/eye/hair color. Six major genes have identified which are responsible to produce variation in coloration: HERC2, OCA2, TYR, MC1R, SLC45A2, and SLC24A2. In this paper, Apache Spark and Python on a virtual machine running Ubuntu have been used to analyze the variation considering the genomic regions associated with these genes. The study included different populations which have been categorized into three groups. First group is the ‘sample population’ that includes five subpopulations, Mexican, Han Chinese, Yoruba, British, and Japanese. People from these populations can be easily distinguished on the basis of skin/eye/hair color. The second group includes five super populations of the world from different continents, viz. African, American, European, East Asian, and South Asian. This will provide the intercontinent analysis. The third group is ‘South-Asian population’ that includes five subpopulations from South-Asian subcontinent, viz. Punjabi, Gujarati, Tamil, Telugu, and Bengali, for the study in geographically closer populations. These populations are expected to show some degree of variation in the genomic regions in these six genes. Our results indicated that three different populations showed variations in different genes. First group of population depicted the maximum diversity in ‘TYR’ gene followed by SLC45A2. This SLC45A2 gene was most diverse in continental population, whereas the third group showed similar diversity across all the six genes. This implicates that the specific population shows diversity in specific genes and also proves that Apache Spark has great potential in assessing nucleotide diversity.

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Authors and Affiliations

  1. University of Kentucky, Lexington, KY, USA

    Ankur Saxena, Shivani Chandra, Alka Grover & Lakshay Anand

  2. School of Life Sciences, Starex University, Gurugram, India

    Shalini Jauhari

Authors
  1. Ankur Saxena
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  2. Shivani Chandra
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  3. Alka Grover
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  4. Lakshay Anand
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  5. Shalini Jauhari
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Corresponding author

Correspondence to Shivani Chandra .

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Editors and Affiliations

  1. Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology, New Delhi, Delhi, India

    Ashish Khanna

  2. Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology, New Delhi, Delhi, India

    Deepak Gupta

  3. Department of Computer Science and Engineering, Christ University, Bangalore, India

    Siddhartha Bhattacharyya

  4. Department of Computer Science, VŠB—Technical University of Ostrava, Ostrava, Czech Republic

    Vaclav Snasel

  5. Department of Computer Science, VŠB—Technical University of Ostrava, Ostrava, Czech Republic

    Jan Platos

  6. Faculty of Computers and Information, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

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Saxena, A., Chandra, S., Grover, A., Anand, L., Jauhari, S. (2020). Genetic Variance Study in Human on the Basis of Skin/Eye/Hair Pigmentation Using Apache Spark. In: Khanna, A., Gupta, D., Bhattacharyya, S., Snasel, V., Platos, J., Hassanien, A. (eds) International Conference on Innovative Computing and Communications. Advances in Intelligent Systems and Computing, vol 1087. Springer, Singapore. https://doi.org/10.1007/978-981-15-1286-5_31

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