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Related Concept Videos

Genetic Screens02:46

Genetic Screens

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 result in visible changes...
Genome-wide Association Studies-GWAS01:11

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...
Multiple Allele Traits01:49

Multiple Allele Traits

The Concept of Multiple Allelism
Multiple Allele Traits01:49

Multiple Allele Traits

The Concept of Multiple Allelism
Polygenic Traits01:18

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...
Polygenic Traits01:18

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: Jul 10, 2026

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

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

Published on: June 21, 2018

A fast boosting-based screening method for large-scale association study in complex traits with genetic

Lu-Yong Wang1, D Fasulo

  • 1Integrated Data Syst. Dept., Siemens Corp. Res. Inc., Princeton, NJ 08540, USA. luyong.wang@siemens.com

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
|October 20, 2007
PubMed
Summary

This study introduces a novel boosting-based method for rapid screening of single nucleotide polymorphisms (SNPs) in large-scale complex disease studies. The method efficiently identifies potential disease-associated SNPs, even with genetic heterogeneity, for further analysis.

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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

Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • Genome-wide association studies (GWAS) generate vast single nucleotide polymorphisms (SNPs) data for complex diseases.
  • Traditional univariate and model-based methods struggle with large datasets and genetic heterogeneity.
  • Existing random forest methods are effective but may not be sufficiently fast for extremely large datasets.

Purpose of the Study:

  • To develop a rapid and robust SNP screening method for large-scale GWAS.
  • To address the challenge of identifying disease-susceptible SNPs with small marginal effects.
  • To account for genetic heterogeneity in complex trait association analysis.

Main Methods:

  • Proposed a novel boosting-based method for SNP screening.
  • Evaluated the method's performance on large-scale datasets, including Affymetrix Human Mapping 100K GeneChip data.
  • Compared the boosting-based method with existing univariate and random forest approaches.

Main Results:

  • The boosting-based method offers a faster alternative for screening large SNP datasets.
  • Demonstrated the method's effectiveness in identifying candidate SNPs, even in the presence of genetic heterogeneity.
  • The proposed tool efficiently narrows down candidate SNPs for subsequent complex computational modeling.

Conclusions:

  • Boosting-based methods provide a computationally efficient approach for large-scale SNP screening in GWAS.
  • This method enhances the ability to detect disease-associated SNPs in complex genetic architectures.
  • The developed tool facilitates more tractable downstream analyses for complex disease genetics.