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Related Concept Videos

Behavioral Genetics and Its Designs01:23

Behavioral Genetics and Its Designs

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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Background and Environment Affect Phenotype

Although the genetic makeup of an organism plays a major role in determining the phenotype, there are also several environmental factors, such as temperature, oxygen availability, presence of mutagens, that can alter an organism’s phenotype.
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Epistasis Analysis

Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...
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In statistics, correlation describes the degree of association between two variables. In the subfield of linear regression, correlation is mathematically expressed by the correlation coefficient, which describes the strength and direction of the relationship between two variables. The coefficient is symbolically represented by 'r' and ranges from -1 to +1. A positive value indicates a positive correlation where the two variables move in the same direction. A negative value suggests a negative...
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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.
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Polygenic Traits

When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...

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Related Experiment Video

Updated: May 12, 2026

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization
08:27

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization

Published on: July 27, 2021

Efficient techniques for genotype-phenotype correlational analysis.

Subrata Saha1, Sanguthevar Rajasekaran, Jinbo Bi

  • 1Department of Computer Science and Engineering, University of Connecticut, Storrs, Connecticut, USA.

BMC Medical Informatics and Decision Making
|April 6, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces novel algorithms for selecting informative Single Nucleotide Polymorphisms (SNPs) for phenotypic classification, offering improved accuracy and speed over existing methods.

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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

Published on: June 21, 2018

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Single Nucleotide Polymorphisms (SNPs) are crucial genetic markers.
  • Conventional SNP analysis methods face challenges in runtime and efficiency.
  • There is a need for scalable and reliable SNP selection for phenotypic classification.

Purpose of the Study:

  • To develop efficient, scalable, and reliable algorithms for selecting a subset of SNPs.
  • To improve phenotypic classification accuracy using selected SNPs.
  • To address limitations of existing SNP analysis techniques.

Main Methods:

  • Utilized gene selection and random projections for SNP identification.
  • Applied random projections to reduce data dimensionality while preserving distances.
  • Employed gene selection on projected data to find relevant SNPs.

Main Results:

  • Proposed algorithms demonstrated superior performance compared to Multifactor Dimensionality Reduction (MDR) and Principal Component Analysis (PCA).
  • Achieved higher accuracy and reduced run times in experimental evaluations.
  • Validated the effectiveness of random projections and gene selection for SNP analysis.

Conclusions:

  • Random projections effectively overcome the curse of dimensionality in high-dimensional SNP data.
  • The proposed unique mechanism offers high accuracy with low run times.
  • This approach provides a novel and efficient method for genotype-phenotype correlation studies.