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Genome-wide Association Studies-GWAS

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.
GWAS does not require the identification of the target gene involved in...

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A Strategy to Identify de Novo Mutations in Common Disorders such as Autism and Schizophrenia

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Published on: June 15, 2011

Detecting pathogenic variants in autoimmune diseases using high-throughput sequencing.

Matt A Field^1,2

¹Centre for Tropical Bioinformatics and Molecular Biology, Australian Institute of Tropical Health and Medicine, James Cook University, Cairns, QLD, Australia.

Immunology and Cell Biology

|July 6, 2020

Summary

This summary is machine-generated.

Advances in human genome sequencing now enable rapid, affordable analysis. This review explores methods for identifying genetic variants in autoimmune diseases, crucial for precision medicine.

Keywords:

Autoimmune diseases SNV high-throughput sequencing pathogenic variant variant annotation variant detection

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Area of Science:

Genomics
Immunology
Medical Genetics

Background:

Human genome sequencing costs have dramatically decreased, enabling large-scale data generation.
Vast human genetic variation databases and reference genomes aid in identifying disease-causing variants.
Sequencing is increasingly vital for understanding the genetic basis of autoimmune diseases.

Purpose of the Study:

To review current methodologies for identifying pathogenic variants in autoimmune diseases.
To discuss sequencing technologies and bioinformatic strategies for variant detection.
To highlight the importance of robust workflows for precision medicine in autoimmune disorders.

Main Methods:

Review of recent literature on sequencing technologies and bioinformatic approaches.
Analysis of strategies for variant identification in polygenic autoimmune diseases.
Examination of challenges in establishing gold-standard methodologies for pathogenic variant detection.

Main Results:

Significant progress has been made in generating high-quality human sequence data.
Databases of population and disease-causing variation are expanding.
Despite advances, standardized methods for identifying pathogenic variants in autoimmune diseases are still lacking.

Conclusions:

Reliable sequencing and analytic workflows are essential for diagnosing autoimmune diseases.
Identifying pathogenic variants is critical for advancing precision medicine in autoimmune disorders.
Further development is needed to establish gold-standard methods for variant detection in complex diseases.