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Related Concept Videos

Heritability01:06

Heritability

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" a trait is,...
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...
Hardy-Weinberg Principle01:49

Hardy-Weinberg Principle

Diploid organisms have two alleles of each gene, one from each parent, in their somatic cells. Therefore, each individual contributes two alleles to the gene pool of the population. The gene pool of a population is the sum of every allele of all genes within that population and has some degree of variation. Genetic variation is typically expressed as a relative frequency, which is the percentage of the total population that has a given allele, genotype or phenotype.In the early 20th century,...
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Genetic Lingo

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Genome Copying Errors02:46

Genome Copying Errors

DNA replication is a well-evolved process that copies millions of base pairs with high fidelity during each cell division. Occasionally a wrong base or a long stretch of wrong bases may get added to the daughter strands. If the errors are left unchecked, cells might accumulate several mutations that might endanger their  survival. Therefore, the copying errors are checked and repaired at three levels.
Law of Segregation01:49

Law of Segregation

When crossing pea plants, Mendel noticed that one of the parental traits would sometimes disappear in the first generation of offspring, called the F1 generation, and could reappear in the next generation (F2). He concluded that one of the traits must be dominant over the other, thereby causing masking of one trait in the F1 generation. When he crossed the F1 plants, he found that 75% of the offspring in the F2 generation had the dominant phenotype, while 25% had the recessive phenotype.

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Correcting away the hidden heritability.

Scott M Williams1, Jonathan L Haines

  • 1Center for Human Genetics Research, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN. scott.williams@chgr.mc.vanderbilt.edu

Annals of Human Genetics
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Summary
This summary is machine-generated.

Stringent multiple comparison corrections in genetic studies lead to false negatives, hindering complex disease research. Overly conservative methods slow progress by discarding potentially real genetic signals.

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Area of Science:

  • Genetics
  • Epidemiology
  • Bioinformatics

Background:

  • Genome-wide association studies (GWAS) generate large datasets, necessitating multiple comparison corrections.
  • Current publication standards demand stringent statistical correction and independent replication for genetic association findings.
  • This rigorous approach can lead to inflated Type 2 error rates (false negatives), masking true genetic associations.

Purpose of the Study:

  • To critically evaluate the impact of stringent multiple comparison correction methods in genetic epidemiology.
  • To advocate for a re-evaluation of current publication standards regarding statistical rigor and replication requirements.
  • To highlight the potential for overly conservative approaches to impede research progress in complex disease genetics.

Main Methods:

  • The study reviews current practices in statistical correction for multiple comparisons in GWAS.
  • It analyzes the consequences of stringent correction thresholds on the identification of true genetic associations.
  • The authors discuss the feasibility and cost-effectiveness of high-density follow-up experiments.

Main Results:

  • Overly stringent corrections in genetic studies result in a high rate of false negatives.
  • Potentially significant genetic associations are discarded, slowing down the identification of causal variants.
  • The current paradigm hinders the advancement of research into complex diseases.

Conclusions:

  • Current multiple comparison correction standards in genetic epidemiology are overly conservative.
  • Relaxing these standards, supported by feasible follow-up studies, can accelerate the discovery of disease-associated alleles.
  • Revising publication guidelines is crucial for efficient progress in complex disease research.