Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies
  1. Home
  3. Population-aware Permutation-based Significance Thresholds For Genome-wide Association Studies.
  1. Home
  3. Population-aware Permutation-based Significance Thresholds For Genome-wide Association Studies.

Related Concept Videos

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

12.4K
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...
12.4K
Significance Testing: Overview01:04

Significance Testing: Overview

3.3K
Significance testing is a set of statistical methods used to test whether a claim about a parameter is valid. In analytical chemistry, significance testing is used primarily to determine whether the difference between two values comes from determinate or random errors. The effect of a particular change in the measurement protocol, analyst, or sample itself can cause a deviation from the expected result. In the case of a suspected deviation/outlier, we need to be able to confirm mathematically...
3.3K
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

17.2K
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%...
17.2K
Wilcoxon Signed-Ranks Test for Median of Single Population01:14

Wilcoxon Signed-Ranks Test for Median of Single Population

101
The Wilcoxon signed-rank test for the median of a single population is a nonparametric test used to evaluate whether the median of a population differs from a specified value. Unlike parametric tests, it does not require data to follow a normal distribution, making it suitable for non-normal or small samples. The test begins by calculating the difference (d) between each observation and the hypothesized median. The absolute values of these differences are ranked in ascending order, with ties...
101
Wald-Wolfowitz Runs Test II01:17

Wald-Wolfowitz Runs Test II

179
The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and...
179

Related Experiment Video

Infinium Assay for Large-scale SNP Genotyping Applications
13:33

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

38.9K

Population-aware permutation-based significance thresholds for genome-wide association studies.

Maura John1,2, Arthur Korte3, Marco Todesco4,5,6

  • 1Technical University of Munich, TUM Campus Straubing for Biotechnology and Sustainability, Bioinformatics, 94315 Straubing, Germany.

Bioinformatics Advances
|December 16, 2024

View abstract on PubMed

Summary
This summary is machine-generated.

permGWAS2 improves genome-wide association studies (GWAS) by preserving population structure during permutation testing and optimizing computations. This method reduces false discoveries and identifies novel trait associations in complex populations.

More Related Videos

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
12:39

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

Published on: December 10, 2012

11.3K
Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
11:35

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

Published on: August 21, 2016

12.9K

Related Experiment Videos

Infinium Assay for Large-scale SNP Genotyping Applications
13:33

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

38.9K
A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
12:39

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

Published on: December 10, 2012

11.3K
Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
11:35

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

Published on: August 21, 2016

12.9K

Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • Permutation-based significance thresholds offer a robust alternative to Bonferroni correction in genome-wide association studies (GWAS), especially with skewed phenotype distributions.
  • The permGWAS method introduced efficient batch-wise computation but suffered from redundant calculations and disrupted population structure.
  • Traditional permutation methods that only permute phenotypes can break underlying population structures, leading to inaccurate results.

Purpose of the Study:

  • To develop an improved permutation-based GWAS method (permGWAS2) that preserves population structure and optimizes computational efficiency.
  • To reduce redundant computations and enhance the accuracy of significance thresholds in GWAS.
  • To identify novel genetic associations with adaptive traits and filter out false positives.

Main Methods:

  • Implemented permGWAS2, a novel method utilizing block matrix decomposition for optimized permutation computations.
  • Preserved population structure throughout the permutation process, unlike traditional methods.
  • Validated permGWAS2 on synthetic datasets and re-analyzed a wild sunflower (Helianthus annuus L.) dataset with 86 phenotypic traits.

Main Results:

  • permGWAS2 demonstrated a lower false discovery rate for skewed phenotypes compared to permGWAS and Bonferroni correction on synthetic data.
  • Analysis of the wild sunflower dataset identified numerous novel associations with putatively adaptive traits.
  • Several likely false-positive associations previously reported were successfully removed, increasing confidence in the findings.

Conclusions:

  • permGWAS2 offers a significant advancement in GWAS methodology by maintaining population structure and improving computational efficiency.
  • The method provides more accurate significance thresholds, leading to more reliable identification of genetic associations.
  • permGWAS2 is a valuable open-source tool for genetic research, particularly for studies with complex population structures and skewed phenotypes.