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Related Concept Videos

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

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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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
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Comparing Copy Number Variations and SNPs02:26

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Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
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Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

Identifying rare variants associated with complex traits via sequencing.

Bingshan Li1, Dajiang J Liu, Suzanne M Leal

  • 1Department of Molecular Physiology and Biophysics, Center for Human Genetics Research, Vanderbilt University, Nashville, Tennessee, USA.

Current Protocols in Human Genetics
|July 16, 2013
PubMed
Summary
This summary is machine-generated.

Identifying rare genetic variants associated with complex traits is crucial. New statistical methods aggregate rare variants, offering improved analysis for next-generation sequencing data.

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Last Updated: May 9, 2026

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Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and DNA-affinity Precipitation Assay (DAPA)
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Area of Science:

  • Genetics
  • Bioinformatics
  • Statistical Genetics

Background:

  • Genome-wide association studies (GWAS) excel at common variant detection.
  • Growing interest in low-frequency and rare variants for complex traits.
  • Next-generation sequencing (NGS) enables comprehensive genetic variation analysis.

Purpose of the Study:

  • To describe key concepts in rare variant association for complex traits.
  • To survey recent statistical methods for rare variant analysis.
  • To provide practical guidance for NGS data analysis in rare variant identification.

Main Methods:

  • Review of statistical methodologies for rare variant association.
  • Discussion of aggregation-based testing strategies.
  • Analysis of statistical power under various scenarios.

Main Results:

  • Traditional methods are ineffective for rare variant association due to low frequency and allelic heterogeneity.
  • New methods aggregate multiple rare variants for enhanced detection power.
  • Guidance provided for practical NGS data analysis.

Conclusions:

  • Rare variants play a significant role in complex traits.
  • Novel statistical approaches are essential for rare variant discovery.
  • NGS data combined with advanced methods facilitates identification of rare variant associations.