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Related Concept Videos

Genomics02:02

Genomics

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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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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Updated: Oct 19, 2025

A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes
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GAMUT: A genomics big data management tool.

E P Ramakrishnan1, Saurabh Gupta, Renu Gadhari

  • 1High Performance Computing-Medical and Bioinformatics Applications Group, Centre for Development of Advanced Computing, Innovation Park, Panchavati, Pashan, Pune 411008, India.

Journal of Biosciences
|September 21, 2021
PubMed
Summary
This summary is machine-generated.

GAMUT efficiently compares Single Nucleotide Polymorphisms (SNPs) across large genomic datasets. This big data tool aids in identifying population-differentiating variants for genotype-phenotype studies.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Single Nucleotide Polymorphisms (SNPs) are crucial for understanding genotype-phenotype relationships.
  • Efficient comparison of SNPs across large genomic datasets is essential for population genetics and variant cataloging.

Purpose of the Study:

  • To develop an efficient big data solution for comparing SNPs across large genomic datasets.
  • To provide a tool for identifying population-differentiating variants.

Main Methods:

  • Developed GAMUT (Genomics bigdAta Management Tool), a client-server application with MongoDB backend and JSF/PrimeFaces frontend.
  • Utilized Spark for parallel data uploading and a partition-based approach for sample comparison.
  • Implemented dynamic querying options (text, chromosome position, gene name) and data visualization (charts, tables).

Main Results:

  • GAMUT enables efficient run-time comparison of SNPs across large, partitioned datasets.
  • The tool supports dynamic querying and provides downloadable results in various formats (text, HTML, JSON).
  • GAMUT is deployable on WildFly server or as a Docker container.

Conclusions:

  • GAMUT offers an effective big data solution for SNP analysis and comparison.
  • The tool facilitates genotype-phenotype studies by identifying key differentiating variants.
  • GAMUT supports diverse downstream analyses through flexible data output and querying capabilities.