Evidence map›Paper›PMID 22678112›Full record

ArticleHuman heredity2012

Two-stage extreme phenotype sequencing design for discovering and testing common and rare genetic variants: efficiency and power.

Guolian Kang, Dongyu Lin, Hakon Hakonarson, Jinbo Chen

Abstract read
In one paragraph

Article in Human heredity, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

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

  1. Pooled it
  2. High-Penetrance Rare Variants Underlying Familial Lung Cancer Risk: Insights From Genetic Epidemiology of Lung Cancer Consortium.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Phenotypic extremes in rare variant study designs.European journal of human genetics : EJHG · 2016
    Article
  9. Focused Analysis of Exome Sequencing Data for Rare Germline Mutations in Familial and Sporadic Lung Cancer.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2016
    Article
  10. Article
  11. Review
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

4 authors.

Guolian KangDepartment of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA 19104, USA.
Dongyu Lin
Hakon Hakonarson
Jinbo Chen

Funding

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 in Genetic Epidemiology ResearchR01ES016626 · NIEHS · UNIVERSITY OF PENNSYLVANIA · PI CHEN, JINBO · 2008 to 2012
$1.6M
A partially Linear Tree-based Regression Model for Assessing Complex Joint Gene-gR03CA128071 · NCI · UNIVERSITY OF PENNSYLVANIA · PI CHEN, JINBO · 2007 to 2008
$157k
NCI NIH HHS R03 CA128071NIEHS NIH HHS R01 ES016626NIGMS NIH HHS R01 GM031575
6 · The paper itself

Abstract

Next-generation sequencing technology provides an unprecedented opportunity to identify rare susceptibility variants. It is not yet financially feasible to perform whole-genome sequencing on a large number of subjects, and a two-stage design has been advocated to be a practical option. In stage I, variants are discovered by sequencing the whole genomes of a small number of carefully selected individuals. In stage II, the discovered variants of a large number of individuals are genotyped to assess associations. Individuals with extreme phenotypes are typically selected in stage I. Using simulated data for unrelated individuals, we explore two important aspects of this two-stage design: the efficiency of discovering common and rare single-nucleotide polymorphisms (SNPs) in stage I and the impact of incomplete SNP discovery in stage I on the power of testing associations in stage II. We applied a sum test and a sum of squared score test for gene-based association analyses evaluating the power of the two-stage design. We obtained the following results from extensive simulation studies and analysis of the GAW17 dataset. When individuals with trait values more extreme than the 99.7-99th quantile were included in stage I, the two-stage design could achieve the same power as or even higher than the one-stage design if the rare causal variants had large effect sizes. In such design, fewer than half of the total SNPs including more than half of the causal SNPs were discovered, which included nearly all SNPs with minor allele frequencies (MAFs) ≥5%, more than half of the SNPs with MAFs between 1% and 5%, and fewer than half of the SNPs with MAFs <1%. Although a one-stage design may be preferable to identify multiple rare variants having small to moderate effect sizes, our observations support using the two-stage design as a cost-effective option for next-generation sequencing studies.

Indexed as

Genetic VariationGenome-Wide Association StudyModels, GeneticPhenotypePolymorphism, Single NucleotideAlgorithmsComputer SimulationGenotypeHumansLinkage Disequilibrium

Identifiers

PMID22678112
PMCPMC3558993

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.