PT  - JOURNAL ARTICLE
AU  - Hon-Cheong So
AU  - Pak C. Sham
TI  - SumVg: Total heritability explained by all variants in genome-wide association studies based on summary statistics with standard error estimates
AID  - 10.1101/016857
DP  - 2015 Jan 01
TA  - bioRxiv
PG  - 016857
4099  - http://biorxiv.org/content/early/2015/03/22/016857.short
4100  - http://biorxiv.org/content/early/2015/03/22/016857.full
AB  - 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-totalvgContact pcsham{at}hku.hk, hcso85{at}gmail.com