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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.
GWAS does not require the identification of the target gene involved in...
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Heritability01:06

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Heritability is a statistical concept that measures the degree to which genetic differences among individuals contribute to trait variations within a population. It is a fundamental idea in genetics, often prone to misinterpretation. Heritability is expressed as a percentage, reflecting the proportion of variation in a specific trait across a population that can be linked to genetic differences. However, it's important to understand that heritability does not determine how "genetic"...
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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.
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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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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Behavioral Genetics and Its Designs01:23

Behavioral Genetics and Its Designs

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Behavior genetics explores how genetic inheritance influences human behavior. It focuses on how genes, passed from parents to offspring, contribute to the development of behavioral traits and tendencies. This branch of genetics seeks to understand the complex interplay between inherited genetic factors and environmental influences in shaping our behaviors.
The primary methodologies used in behavior genetics include family studies, twin studies, and adoption studies, each providing unique...
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Incomplete Dominance01:43

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Gregor Mendel's work (1822 - 1884) was primarily focused on pea plants. Through his initial experiments, he determined that every gene in a diploid cell has two variants called alleles inherited from each parent. He suggested that amongst these two alleles, one allele is dominant in character and the other recessive. The combination of alleles determines the phenotype of a gene in an organism.
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Related Experiment Video

Updated: Sep 30, 2025

Infinium Assay for Large-scale SNP Genotyping Applications
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A review of SNP heritability estimation methods.

Mingsheng Tang1, Tong Wang1, Xuefen Zhang2

  • 1Division of Health Statistics, School of Public Health, Shanxi Medical University, No.56 Xin jian South Road, 030001, Shanxi, China.

Briefings in Bioinformatics
|March 15, 2022
PubMed
Summary
This summary is machine-generated.

Statistical methods estimate single nucleotide polymorphism (SNP) heritability, the proportion of phenotypic variance explained by measured SNPs. This review covers methods for continuous and binary traits, focusing on scalability and data types.

Keywords:
SNP heritabilitycomplex phenotypesgenomic predictionmissing heritability

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Area of Science:

  • Genetics
  • Biostatistics
  • Quantitative genetics

Background:

  • Single nucleotide polymorphism (SNP) heritability estimates the genetic contribution to phenotypic variation.
  • Understanding SNP heritability is crucial for dissecting complex trait genetics.

Purpose of the Study:

  • To review statistical methods for estimating SNP heritability.
  • To compare methods based on model assumptions, parameter optimization, and data handling capabilities.

Main Methods:

  • Review of recently developed and commonly used SNP heritability estimation methods.
  • Focus on methods for continuous and binary phenotypes.
  • Evaluation of methods' capacity for multiple phenotypes, longitudinal data, heritability partitioning, and data types (individual vs. summary statistics).

Main Results:

  • Discussion of various SNP heritability estimation techniques.
  • Highlighting methods scalable to large datasets like the UK Biobank.
  • Comparison of methods considering their strengths and limitations.

Conclusions:

  • SNP heritability estimation methods have advanced significantly.
  • The choice of method depends on phenotype type, data availability, and research questions.
  • Scalable methods are essential for analyzing large-scale genetic data.