Evidence map›Paper›PMID 25112185›Full record

ArticleGenetic epidemiology2014

Complex pedigrees in the sequencing era: to track transmissions or decorrelate?

Dalin Li, Jin Zhou, Duncan C Thomas, David W Fardo

Abstract read
In one paragraph

Article in Genetic epidemiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Dalin LiMedical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America; David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, United States of America.
Jin Zhou
Duncan C Thomas
David W Fardo

Funding

WKU Lead Faculty AwardP20GM103436 · NIGMS · UNIVERSITY OF LOUISVILLE · PI Bruce A Mattingly · 2012 to 2026
$60.1M
Transgenic & Knock-out MouseP30DK063491 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PETER J TONTONOZ · 2003 to 2026
$40.4M
GENETIC ANALYSIS OF COMMON DISEASES: AN EVALUATIONR01GM031575 · NIGMS · UNIVERSITY OF TEXAS RIO GRANDE VALLEY · PI ALMASY, LAURA A. · 1985 to 2016
$7.8M
Methods for Pathway Modeling with Application to FolateR01ES019876 · NIEHS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI THOMAS, DUNCAN C. · 2010 to 2014
$2.9M
Statistical Genetics Methods for Mixed PathologiesK25AG043546 · NIA · UNIVERSITY OF KENTUCKY · PI FARDO, DAVID WILLIAM · 2013 to 2015
$445k
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
NHGRI NIH HHS U01 HG005927NIA NIH HHS K25 AG043546NIA NIH HHS K25AG043546NIDDK NIH HHS DK063491NIDDK NIH HHS P30 DK063491NIEHS NIH HHS R01 ES019876NIGMS NIH HHS P20 GM103436NIGMS NIH HHS R01 GM031575
6 · The paper itself

Abstract

Next-generation sequencing (NGS) studies are becoming commonplace, and the NGS field is continuing to develop rapidly. Analytic methods aimed at testing for the various roles that genetic susceptibility plays in disease are also rapidly being developed and optimized. Studies that incorporate large, complex pedigrees are of particular importance because they provide detailed information about inheritance patterns and can be analyzed in a variety of complementary ways. The nine contributions from our Genetic Analysis Workshop 18 working group on family-based tests of association for rare variants using simulated data examined analytic methods for testing genetic association using whole-genome sequencing data from 20 large pedigrees with 200 phenotype simulation replicates. What distinguishes the approaches explored is how the complexities of analyzing familial genetic data were handled. Here, we explore the methods that either harness inheritance patterns and transmission information or attempt to adjust for the correlation between family members in order to utilize computationally and conceptually simpler statistical testing procedures. Although directly comparing these two classes of approaches across contributions is difficult, we note that the two classes balance robustness to population stratification and computational complexity (the transmission-based approaches) with simplicity and increased power, assuming no population stratification or proper adjustment for it (decorrelation approaches).

Indexed as

Genetic Association StudiesPedigreeBlood PressureGenetic LinkageGenetic Predisposition to DiseaseHigh-Throughput Nucleotide SequencingHumansPhenotypePolymorphism, Single NucleotideQuantitative Trait LociSequence Analysis, DNAdecorrelation strategiesfamily-based association testingGenetic Analysis Workshop 18next-generation sequencing

Identifiers

PMID25112185
PMCPMC4272198

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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.