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Genomics02:02

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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
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While every living organism has a genome of some kind (be it RNA, or DNA), there is considerable variation in the sizes of these blueprints. One major factor that impacts genome size is whether the organism is prokaryotic or eukaryotic. In prokaryotes, the genome contains little to no non-coding sequence, such that genes are tightly clustered in groups or operons sequentially along the chromosome. Conversely, the genes in eukaryotes are punctuated by long stretches of non-coding sequence.
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Data collection refers to a systematic way of obtaining, observing, measuring, and analyzing accurate information. Observational studies are one of the most widely used methods of data collection. It involves collecting data by observing the behavior and physical characteristics of a sample without making any modifications to the sample.
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Big Data: Astronomical or Genomical?

Zachary D Stephens1, Skylar Y Lee1, Faraz Faghri2

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Genomics is a rapidly growing Big Data field. By 2025, its data demands in acquisition, storage, distribution, and analysis may surpass those of astronomy, YouTube, and Twitter, requiring new technologies and planning.

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Area of Science:

  • Genomics
  • Big Data Science
  • Computational Biology

Background:

  • Genomics is a rapidly expanding Big Data field.
  • The comparative data demands of genomics against other Big Data domains are not well-established.

Purpose of the Study:

  • To project and compare the Big Data requirements of genomics to other major data-generating domains by 2025.
  • To identify potential technological and planning needs for future genomic data challenges.

Main Methods:

  • Comparative analysis of data acquisition, storage, distribution, and analysis needs.
  • Projection of data demands for genomics, astronomy, YouTube, and Twitter to the year 2025.

Main Results:

  • Genomics is identified as a significant Big Data generator, potentially exceeding other domains analyzed.
  • By 2025, genomics may be on par with or the most demanding domain in terms of data acquisition, storage, distribution, and analysis.
  • The study highlights the 'four-headed beast' nature of genomic data challenges.

Conclusions:

  • Significant advancements in technology and infrastructure are required to meet the escalating computational demands of genomics.
  • Proactive, community-wide planning is essential to address the genomic data challenges of the next decade.