Evidence map›Paper›PMID 23853079›Full record

ReviewCurrent protocols in human genetics2013

Identifying rare variants associated with complex traits via sequencing.

Bingshan Li, Dajiang J Liu, Suzanne M Leal

Abstract readReview
In one paragraph

Review in Current protocols in human genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
–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

26 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. eLife · 2020
    Article
  10. VMAT2 gene (Pharmacogenomics · 2019
    Article
  11. Article
  12. Association ofInternational journal of hypertension · 2019
    Article
  13. Article
  14. Article
  15. Family studies to find rare high risk variants in migraine.The journal of headache and pain · 2017
    Review
  16. Article
  17. Article
  18. Review
  19. Article
  20. 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

3 authors.

Bingshan LiDepartment of Molecular Physiology and Biophysics, Center for Human Genetics Research, Vanderbilt University, Nashville, Tennessee, USA.
Dajiang J Liu
Suzanne M Leal

Funding

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
Design and analysis of sequencing studies for gene mapping in familiesR01HG006857 · NHGRI · VANDERBILT UNIVERSITY · PI LI, BINGSHAN · 2013 to 2016
$1.5M
NHGRI NIH HHS R01 HG006857NHLBI NIH HHS HL102926NHLBI NIH HHS RC2 HL102926NHLBI NIH HHS UC2 HL102926NIMHD NIH HHS MD005964NIMHD NIH HHS RC4 MD005964
6 · The paper itself

Abstract

Although genome-wide association studies have been successful in detecting associations with common variants, there is currently an increasing interest in identifying low-frequency and rare variants associated with complex traits. Next-generation sequencing technologies make it feasible to survey the full spectrum of genetic variation in coding regions or the entire genome. The association analysis for rare variants is challenging, and traditional methods are ineffective, however, due to the low frequency of rare variants, coupled with allelic heterogeneity. Recently a battery of new statistical methods has been proposed for identifying rare variants associated with complex traits. These methods test for associations by aggregating multiple rare variants across a gene or a genomic region or among a group of variants in the genome. In this unit, we describe key concepts for rare variant association for complex traits, survey some of the recent methods, discuss their statistical power under various scenarios, and provide practical guidance on analyzing next-generation sequencing data for identifying rare variants associated with complex traits.

Indexed as

Genetic VariationGenome-Wide Association StudyHigh-Throughput Nucleotide SequencingMultifactorial InheritanceQuantitative Trait, HeritableAlgorithmsChromosome MappingHumansLinkage DisequilibriumModels, Genetic

Identifiers

PMID23853079
PMCPMC3830981

What OpenQuestion holds

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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.