ArticleBioinformatics (Oxford, England)2018
A scalable estimator of SNP heritability for biobank-scale data.
Article in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
40 citing papers in PubMed.
- Spatial co-expression and cell-cell communication inference from spatially resolved transcriptomics with CONCISE.bioRxiv : the preprint server for biology · 2026Article
- Unravelling the genetic architecture of cerebral small vessel disease in the context of stroke.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2026Review
- Genetic prediction with ARG-powered linear algebra.Genetics · 2026Article
- General, orders-of-magnitude faster whole-genome analysis with genotype representation graphs.bioRxiv : the preprint server for biology · 2026Article
- A biobank-scale method for learning modulators of gene-environment interaction underlying human complex traits from multiple environmental exposures.bioRxiv : the preprint server for biology · 2026Article
- Single- and Multi-Trait Genome-Wide Association Analyses Identify the Genetic Loci and Candidate Genes for Growth Traits inAnimals : an open access journal from MDPI · 2026Article
- Leveraging ancestral recombination graphs for scalable mixed-model analysis of complex traits.Cell genomics · 2026Article
- Cross-Ancestry Polygenic Prediction: Comparing Methods and Assessing Transferability Across Traits.Genetic epidemiology · 2026Article
- On ARGs, pedigrees, and genetic relatedness matrices.Genetics · 2026Article
- A biobank-scale test of marginal epistasis reveals genome-wide signals of polygenic interaction effects.Nature genetics · 2025Article
- X-LDR: an atlas of linkage disequilibrium across species.Genome biology · 2025Article
- Comprehensive gene heritability estimation reveals the genetic architecture of rare coding variants underlying complex traits.bioRxiv : the preprint server for biology · 2025Article
- Analytical and computational solution for the estimation of SNP-heritability in biobank-scale and distributed datasets.PLoS computational biology · 2025Article
- Sparse modeling of interactions enables fast detection of genome-wide epistasis in biobank-scale studies.American journal of human genetics · 2025Article
- Precise estimation of in-depth relatedness in biobank-scale datasets using deepKin.Cell reports methods · 2025Article
- The contribution of gametic phase disequilibrium to the heritability of complex traits.Nature genetics · 2025Article
- Article
- A scalable variational inference approach for increased mixed-model association power.Nature genetics · 2025Article
- Efficient large-scale genomic prediction in approximate genome-based kernel model.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Scalable summary-statistics-based heritability estimation method with individual genotype level accuracy.Genome research · 2024Article
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
Motivation: Heritability, the proportion of variation in a trait that can be explained by genetic variation, is an important parameter in efforts to understand the genetic architecture of complex phenotypes as well as in the design and interpretation of genome-wide association studies. Attempts to understand the heritability of complex phenotypes attributable to genome-wide single nucleotide polymorphism (SNP) variation data has motivated the analysis of large datasets as well as the development of sophisticated tools to estimate heritability in these datasets. Linear mixed models (LMMs) have emerged as a key tool for heritability estimation where the parameters of the LMMs, i.e. the variance components, are related to the heritability attributable to the SNPs analyzed. Likelihood-based inference in LMMs, however, poses serious computational burdens. Results: We propose a scalable randomized algorithm for estimating variance components in LMMs. Our method is based on a method-of-moment estimator that has a runtime complexity O(NMB) for N individuals and M SNPs (where B is a parameter that controls the number of random matrix-vector multiplications). Further, by leveraging the structure of the genotype matrix, we can reduce the time complexity to O(NMBmax( log3N, log3M)). We demonstrate the scalability and accuracy of our method on simulated as well as on empirical data. On standard hardware, our method computes heritability on a dataset of 500 000 individuals and 100 000 SNPs in 38 min. Availability and implementation: The RHE-reg software is made freely available to the research community at: https://github.com/sriramlab/RHE-reg.
Indexed as
Identifiers
What OpenQuestion holds
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.