ArticleBMC bioinformatics2021
Boosting heritability: estimating the genetic component of phenotypic variation with multiple sample splitting.
Article in BMC bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Insights into the influence of diet and genetics on feed efficiency and meat production in sheep.Animal genetics · 2024Pooled it
- Local SNP-explained methylation variation reveals genetically anchored and exposure-associated methylation architecture in the human brain.bioRxiv : the preprint server for biology · 2026Article
- Large-scale testing of antimicrobial lethality at single-cell resolution predicts mycobacterial infection outcomes.Nature microbiology · 2026Article
- Optimising machine learning prediction of minimum inhibitory concentrations inMicrobial genomics · 2024Article
- Inferring the heritability of bacterial traits in the era of machine learning.Bioinformatics advances · 2023Review
- Genome-wide association, prediction and heritability in bacteria with application toNAR genomics and bioinformatics · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHeritability is a central measure in genetics quantifying how much of the variability observed in a trait is attributable to genetic differences. Existing methods for estimating heritability are most often based on random-effect models, typically for computational reasons. The alternative of using a fixed-effect model has received much more limited attention in the literature.
resultsIn this paper, we propose a generic strategy for heritability inference, termed as "boosting heritability", by combining the advantageous features of different recent methods to produce an estimate of the heritability with a high-dimensional linear model. Boosting heritability uses in particular a multiple sample splitting strategy which leads in general to a stable and accurate estimate. We use both simulated data and real antibiotic resistance data from a major human pathogen, Sptreptococcus pneumoniae, to demonstrate the attractive features of our inference strategy.
conclusionsBoosting is shown to offer a reliable and practically useful tool for inference about heritability.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.