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Related Concept Videos

Heritability01:06

Heritability

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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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Pleiotropy is the phenomenon in which a single gene impacts multiple, seemingly unrelated phenotypic traits. For example, defects in the SOX10 gene cause Waardenburg Syndrome Type 4, or WS4, which can cause defects in pigmentation, hearing impairments, and an absence of intestinal contractions necessary for elimination. This diversity of phenotypes results from the expression pattern of SOX10 in early embryonic and fetal development. SOX10 is found in neural crest cells that form melanocytes,...
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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.
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Updated: Jun 3, 2025

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
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Refining fine-mapping: Effect sizes and regional heritability.

Christian Benner1, Anubha Mahajan1, Matti Pirinen2,3,4

  • 1Genentech, South San Francisco, California, United States of America.

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|January 9, 2025
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Summary
This summary is machine-generated.

FINEMAP software now better estimates regional heritability by identifying multiple causal genetic variants. This approach captures significantly more heritability than methods focusing on single variants, improving genetic architecture understanding.

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Area of Science:

  • Genetics
  • Statistical Genetics
  • Bioinformatics

Background:

  • Complex traits and diseases are influenced by numerous genetic variants, collectively explaining more phenotypic variance than individually associated variants.
  • Increasing sample sizes enhance the detection and prioritization of specific variants linked to genomic regions and phenotypes.

Purpose of the Study:

  • To extend the FINEMAP software for estimating effect sizes and regional heritability using a probabilistic model with few causal variants per region.
  • To compare FINEMAP's performance against existing variance component (BOLT) and fixed-effect (HESS) models.

Main Methods:

  • Simulated genomic regions using UK Biobank (UKB) data to assess precision and heritability decomposition.
  • Applied FINEMAP, BOLT, and HESS to UKB plasma protein data (2,940 proteins) to evaluate regional heritability capture.

Main Results:

  • FINEMAP demonstrated higher precision and more detailed regional heritability decomposition than BOLT and HESS, especially with few causal variants.
  • FINEMAP identified an average of 2.5 causal variants per association signal, capturing 36% more regional heritability than the top associated variant.
  • FINEMAP captured 13% and 40% more heritability than BOLT and HESS, respectively, in regions with significant heritability contributions.

Conclusions:

  • FINEMAP provides a more refined approach to understanding the genetic architecture of complex traits by accounting for multiple causal variants.
  • The extended FINEMAP offers improved estimation of regional heritability, outperforming established methods like BOLT and HESS in key scenarios.
  • This work clarifies the relationships between FINEMAP, BOLT, and HESS, particularly for inferring variant-level genetic architecture.