Evidence map›Paper›PMID 24360806›Full record

ArticleAmerican journal of human genetics2014

Rare-variant extensions of the transmission disequilibrium test: application to autism exome sequence data.

Zongxiao He, Brian J O'Roak, Joshua D Smith, Gao Wang, Stanley Hooker, Regie Lyn P Santos-Cortez, Biao Li, Mengyuan Kan, Nik Krumm, Deborah A Nickerson and 3 more

Open access · bronzeAbstract read
In one paragraph

Article in American journal of human genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed, 1 pooled it
6.5field-weighted citation impact, top 3% of its field
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

56 citing papers in PubMed, 1 synthesis or guideline pooled it, 79 citations in OpenAlex.

  1. Pooled it
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  7. Genomic analysis of 11,555 probands identifies 60 dominant congenital heart disease genes.Proceedings of the National Academy of Sciences of the United States of America · 2025
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  15. Rare genetic variants inmedRxiv : the preprint server for health sciences · 2023
    Article
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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

13 authors at 2 institutions in 1 country.

Zongxiao HeCenter for Statistical Genetics, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.
Brian J O'RoakDepartment of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA.
Joshua D SmithDepartment of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA.
Gao WangCenter for Statistical Genetics, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.
Stanley HookerCenter for Statistical Genetics, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.
Regie Lyn P Santos-CortezCenter for Statistical Genetics, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.
Biao LiCenter for Statistical Genetics, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.
Mengyuan KanCenter for Statistical Genetics, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.
Nik KrummDepartment of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA.
Deborah A NickersonDepartment of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA.
Jay ShendureDepartment of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA.
Evan E EichlerDepartment of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA.
Suzanne M LealCenter for Statistical Genetics, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA. Electronic address: sleal@bcm.edu.
Baylor College of Medicine · USUniversity of Washington · US

Funding

University of Washington Medical Scientist Training Program: MD/PhDT32GM007266 · NIGMS · UNIVERSITY OF WASHINGTON · PI HORWITZ, MARSHALL S. · 1985 to 2023
$30.4M
UW Center for Mendelian GenomicsU54HG006493 · NHGRI · UNIVERSITY OF WASHINGTON · PI BAMSHAD, MICHAEL JOSEPH, NICKERSON, DEBORAH A · 2012 to 2015
$20.0M
UW Center for Mendelian GenomicsUM1HG006493 · NHGRI · UNIVERSITY OF WASHINGTON · PI BAMSHAD, MICHAEL JOSEPH, LEAL, SUZANNE M · 2016 to 2020
$15.3M
Northwest Genomics CenterUC2HL102926 · NHLBI · UNIVERSITY OF WASHINGTON · PI GREEN, PHILIP P, NICKERSON, DEBORAH A · 2010 to 2010
$14.0M
Minority Health-GRID Network: A Genomics Resource for Health Disparity ResearchRC4MD005964 · NIMHD · MOREHOUSE SCHOOL OF MEDICINE · PI DAVIS, ROBERT LOWELL, NICKERSON, DEBORAH A · 2010 to 2010
$13.3M
Northwest Genomics CenterRC2HL102926 · NHLBI · UNIVERSITY OF WASHINGTON · PI GREEN, PHILIP P, NICKERSON, DEBORAH A · 2009 to 2009
$11.0M
PROGRAM IN HUMAN MOLECULAR GENETICST32GM008307 · NIGMS · BAYLOR COLLEGE OF MEDICINE · PI SHAULSKY, GAD · 1990 to 2020
$6.6M
Genomic Identification of Autism LociR01HD065285 · NICHD · UNIVERSITY OF WASHINGTON · PI EICHLER, EVAN · 2009 to 2010
$2.6M
Howard Hughes Medical InstituteNHGRI NIH HHS HG006493NHGRI NIH HHS U54 HG006493NHGRI NIH HHS UM1 HG006493NHLBI NIH HHS HL102926NHLBI NIH HHS RC2 HL102926NHLBI NIH HHS UC2 HL102926NICHD NIH HHS HD065285NICHD NIH HHS R01 HD065285NIGMS NIH HHS T32 GM007266NIGMS NIH HHS T32 GM008307NIMHD NIH HHS MD005964NIMHD NIH HHS RC4 MD005964
6 · The paper itself

Abstract

Many population-based rare-variant (RV) association tests, which aggregate variants across a region, have been developed to analyze sequence data. A drawback of analyzing population-based data is that it is difficult to adequately control for population substructure and admixture, and spurious associations can occur. For RVs, this problem can be substantial, because the spectrum of rare variation can differ greatly between populations. A solution is to analyze parent-child trio data, by using the transmission disequilibrium test (TDT), which is robust to population substructure and admixture. We extended the TDT to test for RV associations using four commonly used methods. We demonstrate that for all RV-TDT methods, using proper analysis strategies, type I error is well-controlled even when there are high levels of population substructure or admixture. For trio data, unlike for population-based data, RV allele-counting association methods will lead to inflated type I errors. However type I errors can be properly controlled by obtaining p values empirically through haplotype permutation. The power of the RV-TDT methods was evaluated and compared to the analysis of case-control data with a number of genetic and disease models. The RV-TDT was also used to analyze exome data from 199 Simons Simplex Collection autism trios and an association was observed with variants in ABCA7. Given the problem of adequately controlling for population substructure and admixture in RV association studies and the growing number of sequence-based trio studies, the RV-TDT is extremely beneficial to elucidate the involvement of RVs in the etiology of complex traits.

Indexed as

ExomeGenetic VariationLinkage DisequilibriumAllelesAutistic DisorderComputer SimulationGene FrequencyGenetic Association StudiesGenetic Predisposition to DiseaseHaplotypesHumansModels, GeneticPhenotypeSequence Analysis, DNA

Identifiers

PMID24360806
PMCPMC3882934
OpenAlexW1964351947

What OpenQuestion holds

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Registered trials

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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.