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Related Concept Videos

Genome-wide Association Studies-GWAS01:11

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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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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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The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
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Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
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A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
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Interactive Exploration, Analysis, and Visualization of Complex Phenome-Genome Datasets with ASPIREdb.

Powell Patrick Cheng Tan1, Sanja Rogic1, Anton Zoubarev1

  • 1Michael Smith Laboratories and Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada.

Human Mutation
|May 10, 2016
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Summary

ASPIREdb is a web application that helps researchers analyze genetic variants and phenotypes for complex disorders. It facilitates variant annotation, querying, and collaborative analysis, simplifying the identification of disease-causing mutations.

Keywords:
WESWGScomputational biologygenotype-phenotypevisualizationwhole-exome sequencingwhole-genome sequencing

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Identifying causal variants for complex genetic disorders is a significant challenge.
  • Whole-exome and whole-genome sequencing generate large variant datasets requiring sophisticated analysis tools.
  • Effective correlation of genetic variants with subject phenotypes is crucial for interpreting disease-causing mutations.

Purpose of the Study:

  • To develop a user-friendly web application, ASPIREdb, for searching, organizing, analyzing, and visualizing genetic variants and associated phenotypes.
  • To enable researchers to annotate variants using public databases and build queries for identifying subjects or variants of interest.
  • To facilitate collaborative research by allowing projects to be shared among investigators.

Main Methods:

  • Development of a web application (ASPIREdb) integrating variant and phenotype data.
  • Implementation of variant annotation using publicly available reference databases.
  • Inclusion of query building, burden analysis, and reporting tools for data investigation.
  • Facilitation of project sharing for collaborative data annotation and analysis.

Main Results:

  • ASPIREdb provides a platform for researchers to search, organize, analyze, and visualize genetic variants and phenotypes.
  • The application allows for variant annotation, powerful query construction, and collaborative project management.
  • Demonstrated functionality using publicly available datasets, showcasing its utility for researchers without specialized bioinformatics expertise.

Conclusions:

  • ASPIREdb simplifies the complex process of identifying disease-causing genetic variants by integrating variant and phenotype data analysis.
  • The application enhances collaborative research efforts in genomics and disease genetics.
  • ASPIREdb empowers researchers to interpret genetic findings and advance the study of complex genetic disorders.