Sign in
GenomicsbioRxiv

SumVg: Total heritability explained by all variants in genome-wide association studies based on summary statistics with standard error estimates

Hon-Cheong SO, Pak C. SHAM

Abstract

Genome-wide association studies (GWAS) have become increasingly popular these days and one of the key questions is how much heritability could be explained by all variants in GWAS. We have previously proposed an approach to answer this question, based on recovering the \"true\" z-statistics from a set of observed z-statistics. Only summary statistics are required. However, methods for standard error (SE) estimation are not available yet, thereby limiting the interpretation of the results. In this study we developed resampling-based approaches to estimate the SE and the methods are implemented in an R package. We found that delete-d-jackknife and parametric bootstrap approaches provide good estimates of the SE. Methods to compute the sum of heritability explained and the corresponding SE are implemented in the R package SumVg, available at https://sites.google.com/site/honcheongso/software/var-totalvg\n\nContactpcsham@hku.hk, hcso85@gmail.com

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISSalehi '23Schwartzman '17Lee '14Jeong '24Laville '18Holmes '19
71% semantic matchGenetics
Ehsan Salehi·bioRxiv·Oct 2, 2023