Evidence map›Paper›PMID 25568282›Full record

ArticleBioinformatics (Oxford, England)2015

A haplotype-based framework for group-wise transmission/disequilibrium tests for rare variant association analysis.

Rui Chen, Qiang Wei, Xiaowei Zhan, Xue Zhong, James S Sutcliffe, Nancy J Cox, Edwin H Cook, Chun Li, Wei Chen, Bingshan Li

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Bioinformatics (Oxford, England), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
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

10 authors.

Rui ChenDepartment of Molecular Physiology and Biophysics, Vanderbilt University, TN, 37221, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, TN, 37221, USA, Department of Medicine, University of Chicago, Chicago, IL, USA, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.
Qiang WeiDepartment of Molecular Physiology and Biophysics, Vanderbilt University, TN, 37221, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, TN, 37221, USA, Department of Medicine, University of Chicago, Chicago, IL, USA, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.
Xiaowei ZhanDepartment of Molecular Physiology and Biophysics, Vanderbilt University, TN, 37221, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, TN, 37221, USA, Department of Medicine, University of Chicago, Chicago, IL, USA, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.
Xue ZhongDepartment of Molecular Physiology and Biophysics, Vanderbilt University, TN, 37221, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, TN, 37221, USA, Department of Medicine, University of Chicago, Chicago, IL, USA, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.
James S SutcliffeDepartment of Molecular Physiology and Biophysics, Vanderbilt University, TN, 37221, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, TN, 37221, USA, Department of Medicine, University of Chicago, Chicago, IL, USA, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.
Nancy J CoxDepartment of Molecular Physiology and Biophysics, Vanderbilt University, TN, 37221, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, TN, 37221, USA, Department of Medicine, University of Chicago, Chicago, IL, USA, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.
Edwin H CookDepartment of Molecular Physiology and Biophysics, Vanderbilt University, TN, 37221, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, TN, 37221, USA, Department of Medicine, University of Chicago, Chicago, IL, USA, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.
Chun LiDepartment of Molecular Physiology and Biophysics, Vanderbilt University, TN, 37221, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, TN, 37221, USA, Department of Medicine, University of Chicago, Chicago, IL, USA, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.
Wei ChenDepartment of Molecular Physiology and Biophysics, Vanderbilt University, TN, 37221, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, TN, 37221, USA, Department of Medicine, University of Chicago, Chicago, IL, USA, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA Department of Molecular Physiology and Biophysics, Vanderbilt University, TN, 37221, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, TN, 37221, USA, Department of Medicine, University of Chicago, Chicago, IL, USA, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.
Bingshan LiDepartment of Molecular Physiology and Biophysics, Vanderbilt University, TN, 37221, USA, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA, Center for Quantitative Sciences, Vanderbilt University, TN, 37221, USA, Department of Medicine, University of Chicago, Chicago, IL, USA, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA, Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA.

Funding

Pilot and Feasibility ProgramP30DK020595 · NIDDK · UNIVERSITY OF CHICAGO · PI Matthew J Brady · 2013 to 2026
$20.9M
Re-Engineering Translational Research at the University of ChicagoUL1TR000430 · NCATS · UNIVERSITY OF CHICAGO · PI SOLWAY, JULIAN · 2012 to 2016
$20.2M
Modeling the temporal succession of phenotypes & environnnental cuesP50MH094267 · NIMH · UNIVERSITY OF CHICAGO · PI RZHETSKY, ANDREY · 2011 to 2015
$10.2M
TRANS STUDIES OF COGNITIVE,AFFECTIVE/NEUROCHEMICAL PROCESSES UNDERLYING INSISTENCP50HD055751 · NICHD · UNIVERSITY OF ILLINOIS AT CHICAGO · PI COOK, EDWIN H · 2007 to 2011
$9.5M
Statistical methods for population and family-based whole-genome sequence dataR01HG007358 · NHGRI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI CHEN, WEI · 2014 to 2018
$1.7M
Design and analysis of sequencing studies for gene mapping in familiesR01HG006857 · NHGRI · VANDERBILT UNIVERSITY · PI LI, BINGSHAN · 2013 to 2016
$1.5M
NCATS NIH HHS UL1 TR000430NHGRI NIH HHS R01 HG006857NHGRI NIH HHS R01HG006857NHGRI NIH HHS R01 HG007358NHGRI NIH HHS R01HG007358NHGRI NIH HHS X01 HG007235NICHD NIH HHS P50 HD055751NIDDK NIH HHS P30 DK020595NIMH NIH HHS P50 MH094267
6 · The paper itself

Abstract

motivationA major focus of current sequencing studies for human genetics is to identify rare variants associated with complex diseases. Aside from reduced power of detecting associated rare variants, controlling for population stratification is particularly challenging for rare variants. Transmission/disequilibrium tests (TDT) based on family designs are robust to population stratification and admixture, and therefore provide an effective approach to rare variant association studies to eliminate spurious associations. To increase power of rare variant association analysis, gene-based collapsing methods become standard approaches for analyzing rare variants. Existing methods that extend this strategy to rare variants in families usually combine TDT statistics at individual variants and therefore lack the flexibility of incorporating other genetic models.

resultsIn this study, we describe a haplotype-based framework for group-wise TDT (gTDT) that is flexible to encompass a variety of genetic models such as additive, dominant and compound heterozygous (CH) (i.e. recessive) models as well as other complex interactions. Unlike existing methods, gTDT constructs haplotypes by transmission when possible and inherently takes into account the linkage disequilibrium among variants. Through extensive simulations we showed that type I error was correctly controlled for rare variants under all models investigated, and this remained true in the presence of population stratification. Under a variety of genetic models, gTDT showed increased power compared with the single marker TDT. Application of gTDT to an autism exome sequencing data of 118 trios identified potentially interesting candidate genes with CH rare variants. AVAILABILITY AND IMPLEMENTATION: We implemented gTDT in C++ and the source code and the detailed usage are available on the authors' website (https://medschool.vanderbilt.edu/cgg). CONTACT: bingshan.li@vanderbilt.edu or wei.chen@chp.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

Genetic VariationHaplotypesLinkage DisequilibriumAutistic DisorderComputer SimulationData Interpretation, StatisticalExomeGenetic Association StudiesHumansModels, GeneticSequence Analysis, DNA

Identifiers

PMID25568282
PMCPMC4410665

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.