ArticleCurrent protocols in human genetics2016
Analysis of Heritability Using Genome-Wide Data.
Article in Current protocols in human genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Genome-wide meta-analysis of phytosterols reveals five novel loci and a detrimental effect on coronary atherosclerosis.Nature communications · 2022Pooled it
- Article
- Variant level heritability estimates of type 2 diabetes in African Americans.Scientific reports · 2024Article
- Heritability Estimation Approaches Utilizing Genome-Wide Data.Current protocols · 2023Review
- Pharmacogenomic and Statistical Analysis.Methods in molecular biology (Clifton, N.J.) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Most analyses of genome-wide association data consider each variant independently without considering or adjusting for the genetic background present in the rest of the genome. New approaches to genome analysis use representations of genomic sharing to better account for confounding factors like population stratification or to directly approximate heritability through the estimated sharing of individuals in a dataset. These approaches use mixed linear models, which relate genotypic sharing to phenotypic sharing, and rely on the efficient computation of genetic sharing among individuals in a dataset. This unit describes the principles and practical application of mixed models for the analysis of genome-wide association study data. © 2016 by John Wiley & Sons, Inc.
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Registered trials
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