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@INPROCEEDINGS{Hecker:145643,
author = {Hecker, J. and Prokopenko, D. and Lange, Christoph and
Loehlein Fier, H.},
title = {${A}18_$ {H}eritability {E}stimation from {S}ummary
{S}tatistics{U}sing {G}eneralized {E}stimating {E}quations},
journal = {Human heredity},
volume = {79},
number = {1},
issn = {0001-5652},
reportid = {DZNE-2020-00973},
pages = {36},
year = {2015},
abstract = {Under the assumption of a polygenic architecture,
Yangshowed for complex traits that the test statistics in
genome-wideassociation studies are expected to be inflated,
even in the absenceof confounding biases like cryptic
relatedness or population stratification (Yang et al.,
2011).In a recently published work, Bulik-Sullivan and
Finucane (Bulik-Sullivan et al., 2015) provide a
methodological approach to differentiate between an
inflation resulting from a polygenic architecture and from
cryptic relatedness by considering all test
statisticssimultaneously. This makes it also possible to
estimate the narrowsense heritability from summary
statistics without requiring individual-level genotype
data.The approach of Bulik-Sullivan and Finucane
(Bulik-Sullivanet al., 2015) estimates so-called LD Scores
from a reference paneland utilizes these quantities as
covariates in a weighted linear regression of the squared
test statistics. Since the test statistics are
notindependent of each other, a bootstrap estimator is
applied to obtain robust standard errors.Building on the
same mean model, our objective is to incorporate more useful
extern information into the estimation in orderto improve
the efficiency of the estimation. In particular, we
dividethe genomic region into blocks of moderate size. For
these blocks,the correlation structure between squared test
statistics can be wellapproximated by LD information from a
reference panel. Our estimation procedure is based on
generalized estimating equations(GEE). We use the LD
information to set up the working-correlation matrices for
each block, whereas we do not require that nearby blocks are
independent. We show that the GEE-related asymptotic results
are still valid under reasonable assumptions. It is
important to note that the working-correlation matrices are
notrequired to be exactly the true correlation matrices in
order to obtain consistent estimates and correct standard
errors.In conclusion, these results imply that our approach
improvesthe heritability estimation framework.},
month = {Apr},
date = {2015-04-16},
organization = {43rd European Mathematical Genetics
Meeting 2015, Brest (France), 16 Apr
2015 - 17 Apr 2015},
cin = {U T4 Researchers - Bonn},
ddc = {610},
cid = {I:(DE-2719)7000008},
pnm = {345 - Population Studies and Genetics (POF3-345)},
pid = {G:(DE-HGF)POF3-345},
typ = {PUB:(DE-HGF)1 / PUB:(DE-HGF)16},
url = {https://pub.dzne.de/record/145643},
}