Estimating realized heritability in panmictic populations
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24510%2F18%3A00006227" target="_blank" >RIV/46747885:24510/18:00006227 - isvavai.cz</a>
Alternative codes found
RIV/60460709:41320/18:78634
Result on the web
<a href="https://syndication.highwire.org/content/doi/10.1534/genetics.117.300508" target="_blank" >https://syndication.highwire.org/content/doi/10.1534/genetics.117.300508</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1534/genetics.117.300508" target="_blank" >10.1534/genetics.117.300508</a>
Alternative languages
Result language
angličtina
Original language name
Estimating realized heritability in panmictic populations
Original language description
Narrow sense heritability (h2) is a key concept in quantitative genetics, as it expresses the proportion of the observed phenotypic variation that is transmissible from parents to offspring. h2 determines the resemblance among relatives, and the rate of response to artificial and natural selection. Classical methods for estimating h2 use random samples of individuals with known relatedness, as well as response to artificial selection, when it is called realized heritability. Here, we present a method for estimating realized h2 based on a simple assessment of a random-mating population with no artificial manipulation of the population structure, and derive SE of the estimates. This method can be applied to arbitrary phenotypic segments of the population (for example, the topranking p parents and offspring), rather than random samples. It can thus be applied to nonpedigreed random mating populations, where relatedness is determined from molecular markers in the p selected parents and offspring, thus substantially saving on genotyping costs. Further, we assessed the method by stochastic simulations, and, as expected from the mathematical derivation, it provides unbiased estimates of h2: We compared our approach to the regression and maximum-likelihood approaches utilizing Galton’s dataset on human heights, and all three methods provided identical results.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10602 - Biology (theoretical, mathematical, thermal, cryobiology, biological rhythm), Evolutionary biology
Result continuities
Project
<a href="/en/project/GA15-00243S" target="_blank" >GA15-00243S: Robust inference on random processes and functional data, with applications mainly in econometrics and finances</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
GENETICS
ISSN
0016-6731
e-ISSN
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Volume of the periodical
208
Issue of the periodical within the volume
1
Country of publishing house
US - UNITED STATES
Number of pages
7
Pages from-to
89-95
UT code for WoS article
000419356300006
EID of the result in the Scopus database
2-s2.0-85040128495