Evidence map›Paper›PMID 24379824›Full record

ReviewFrontiers in genetics2013

Two-phase and family-based designs for next-generation sequencing studies.

Duncan C Thomas, Zhao Yang, Fan Yang

Abstract readReview
In one paragraph

Review in Frontiers in genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

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

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

  1. Pooled it
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  3. Review
  4. Article
  5. 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

3 authors.

Duncan C ThomasDepartment of Preventive Medicine, University of Southern California Los Angeles, CA, USA.
Zhao YangDepartment of Preventive Medicine, University of Southern California Los Angeles, CA, USA.
Fan YangDepartment of Preventive Medicine, University of Southern California Los Angeles, CA, USA.

Funding

USC/NORRIS COMPREHENSIVE CANCER CENTER (CORE) SUPPORTP30CA014089 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Fumito Ito · 1985 to 2026
$181.4M
Translational Research Support CoreP30ES007048 · NIEHS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Joseph Leo Wiemels · 1996 to 2026
$46.4M
USC Consortium:Colorectal Cancer Family RegistryU01CA074799 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI HAILE, ROBERT WILLIAM · 1997 to 2008
$20.4M
Genome-Wide Association Study of Radiation Exposure and Bilateral Breast CancerR01CA129639 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI BERNSTEIN, JONINE L. · 2009 to 2013
$15.6M
Transdisciplinary Studies of Genetic Variation in Colorectal CancerU19CA148107 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI GRUBER, STEPHEN B · 2010 to 2014
$11.1M
Methods for Pathway Modeling with Application to FolateR01ES019876 · NIEHS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI THOMAS, DUNCAN C. · 2010 to 2014
$2.9M
Design and Analysis of 2 Stage GWAS Study Using Next Generation Sequence TechnoloU01HG005927 · NHGRI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI MARJORAM, PAUL · 2010 to 2010
$225k
NCI NIH HHS P30 CA014089NCI NIH HHS R01 CA129639NCI NIH HHS U01 CA074799NCI NIH HHS U19 CA148107NHGRI NIH HHS U01 HG005927NIEHS NIH HHS P30 ES007048NIEHS NIH HHS R01 ES019876
6 · The paper itself

Abstract

The cost of next-generation sequencing is now approaching that of early GWAS panels, but is still out of reach for large epidemiologic studies and the millions of rare variants expected poses challenges for distinguishing causal from non-causal variants. We review two types of designs for sequencing studies: two-phase designs for targeted follow-up of genomewide association studies using unrelated individuals; and family-based designs exploiting co-segregation for prioritizing variants and genes. Two-phase designs subsample subjects for sequencing from a larger case-control study jointly on the basis of their disease and carrier status; the discovered variants are then tested for association in the parent study. The analysis combines the full sequence data from the substudy with the more limited SNP data from the main study. We discuss various methods for selecting this subset of variants and describe the expected yield of true positive associations in the context of an on-going study of second breast cancers following radiotherapy. While the sharing of variants within families means that family-based designs are less efficient for discovery than sequencing unrelated individuals, the ability to exploit co-segregation of variants with disease within families helps distinguish causal from non-causal ones. Furthermore, by enriching for family history, the yield of causal variants can be improved and use of identity-by-descent information improves imputation of genotypes for other family members. We compare the relative efficiency of these designs with those using unrelated individuals for discovering and prioritizing variants or genes for testing association in larger studies. While associations can be tested with single variants, power is low for rare ones. Recent generalizations of burden or kernel tests for gene-level associations to family-based data are appealing. These approaches are illustrated in the context of a family-based study of colorectal cancer.

Indexed as

breast neoplasmscolorectal cancerfamily-based studyrare variant associationsequencingtwo-phase sampling design

Identifiers

PMID24379824
PMCPMC3861783

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.