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Related Concept Videos

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

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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.
GWAS does not require the identification of the target gene involved in...
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Genetic Screens02:46

Genetic Screens

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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.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which...
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Quantifying and Rejecting Outliers: The Grubbs Test01:02

Quantifying and Rejecting Outliers: The Grubbs Test

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Sometimes, a data set can have a recorded numerical observation that greatly  deviates from the rest of the data. Assuming that the data is normally distributed, a statistical method called the Grubbs test can be used to determine whether the observation is truly an outlier.  To perform a two-tailed Grubbs test, first, calculate the absolute difference between the outlier and the mean. Then, calculate the ratio between this difference and the standard deviation of the sample. This...
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Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

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A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
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Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

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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.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
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DNA Microarrays02:34

DNA Microarrays

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Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
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Updated: Aug 2, 2025

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

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Multivariate genome-wide association analysis by iterative hard thresholding.

Benjamin B Chu1, Seyoon Ko1,2, Jin J Zhou2,3

  • 1Department of Computational Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095-1554, United States.

Bioinformatics (Oxford, England)
|April 17, 2023
PubMed
Summary
This summary is machine-generated.

Analyzing multiple traits simultaneously in genome-wide association studies (GWAS) is more effective. A new algorithm, MendelIHT, offers a faster and more accurate approach for multivariate GWAS, improving upon existing methods.

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A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
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A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
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Area of Science:

  • Genetics
  • Computational Biology
  • Statistical Genetics

Background:

  • Simultaneous analysis of multiple correlated traits in genome-wide association studies (GWAS) offers advantages over single-trait analyses.
  • Existing multivariate GWAS methods are often computationally intensive and marker-by-marker, limiting scalability.

Purpose of the Study:

  • To develop and implement an efficient algorithm for multivariate genome-wide association studies.
  • To enable the simultaneous analysis of numerous correlated traits and genetic variants.

Main Methods:

  • A sparsity-constrained regression algorithm based on iterative hard thresholding (IHT) was developed.
  • The algorithm was implemented in a Julia package named MendelIHT.jl.
  • Performance was evaluated using simulations and UK Biobank data.

Main Results:

  • MendelIHT demonstrated comparable true positive rates and lower false positive rates than existing methods like GEMMA and mv-PLINK in simulations.
  • The method achieved significantly faster execution times compared to conventional approaches.
  • Analysis of UK Biobank data showed efficient joint analysis of three and 18 traits, handling large datasets with substantial memory usage.

Conclusions:

  • MendelIHT provides a computationally efficient and accurate solution for multivariate genome-wide association studies.
  • The package facilitates the simultaneous modeling of single nucleotide polymorphisms (SNPs) and multiple traits, advancing genetic research.