Evidence map›Paper›PMID 25519371›Full record

ArticleBMC proceedings2014

Identity-by-descent graphs offer a flexible framework for imputation and both linkage and association analyses.

Elizabeth Marchani Blue, Charles Yk Cheung, Christopher G Glazner, Matthew P Conomos, Steven M Lewis, Serge Sverdlov, Timothy Thornton, Ellen M Wijsman

Abstract read
In one paragraph

Article in BMC proceedings, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Elizabeth Marchani BlueDivision of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA 98195, USA.
Charles Yk CheungDepartment of Biostatistics, University of Washington, Seattle, WA 98195, USA.
Christopher G GlaznerDepartment of Statistics, University of Washington, Seattle, WA 98195, USA.
Matthew P ConomosDepartment of Biostatistics, University of Washington, Seattle, WA 98195, USA.
Steven M LewisDepartment of Statistics, University of Washington, Seattle, WA 98195, USA.
Serge SverdlovDepartment of Statistics, University of Washington, Seattle, WA 98195, USA.
Timothy ThorntonDepartment of Biostatistics, University of Washington, Seattle, WA 98195, USA.
Ellen M WijsmanDivision of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA 98195, USA ; Department of Biostatistics, University of Washington, Seattle, WA 98195, USA.

Funding

THERAPEUTIC EFFECTS OF INTRA-NASAL INSULIN DETEMIRP50AG005136 · NIA · UNIVERSITY OF WASHINGTON · PI GRABOWSKI, THOMAS J. · 1985 to 2019
$57.2M
GENETIC ANALYSIS OF COMMON DISEASES: AN EVALUATIONR01GM031575 · NIGMS · UNIVERSITY OF TEXAS RIO GRANDE VALLEY · PI ALMASY, LAURA A. · 1985 to 2016
$7.8M
Statistical Methods for X-Chromosome Genetic DataP01GM099568 · NIGMS · UNIVERSITY OF WASHINGTON · PI THORNTON, TIMOTHY ALVIN · 2012 to 2016
$7.3M
Methods for the Genetic Epidemiology of Complex TraitsR37GM046255 · NIGMS · UNIVERSITY OF WASHINGTON · PI THOMPSON, ELIZABETH ALISON · 2008 to 2017
$4.2M
2/3 Sequencing Autism Spectrum Disorder Extended PedigreesR01MH094293 · NIMH · UNIVERSITY OF WASHINGTON · PI WIJSMAN, ELLEN M · 2012 to 2016
$1.1M
Identifying Alzheimer's disease genes using genomic and family dataR00AG040184 · NIA · UNIVERSITY OF WASHINGTON · PI BLUE, ELIZABETH ELOYCE · 2013 to 2016
$746k
Statistical Methods for Cancer Genetic Association Studies with Hidden PopulationK01CA148958 · NCI · UNIVERSITY OF WASHINGTON · PI THORNTON, TIMOTHY ALVIN · 2010 to 2014
$682k
Identifying Alzheimer's disease genes using genomic and family dataK99AG040184 · NIA · UNIVERSITY OF WASHINGTON · PI BLUE, ELIZABETH ELOYCE · 2011 to 2012
$180k
6 · The paper itself

Abstract

We demonstrate the flexibility of identity-by-descent (IBD) graphs for genotype imputation and testing relationships between genotype and phenotype. We analyzed chromosome 3 and the first replicate of simulated diastolic blood pressure. IBD graphs were obtained from complete pedigrees and full multipoint marker analysis, facilitating subsequent linkage and other analyses. For rare alleles, pedigree-based imputation using these IBD graphs had a higher call rate than did population-based imputation. Combining the two approaches improved call rates for common alleles. We found it advantageous to incorporate known, rather than estimated, pedigree relationships when testing for association. Replacing missing data with imputed alleles improved association signals as well. Analyses were performed with knowledge of the underlying model.

Identifiers

PMID25519371
PMCPMC4143703

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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.