Evidence map›Paper›PMID 25519335›Full record

ArticleBMC proceedings2014

Use of admixture and association for detection of quantitative trait loci in the Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Ethnic Samples (T2D-GENES) study.

Daniel Yorgov, Karen L Edwards, Stephanie A Santorico

Abstract read
In one paragraph

Article in BMC proceedings, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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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.

Daniel YorgovDepartment of Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80217-3364, USA.
Karen L EdwardsDepartment of Epidemiology, School of Medicine, University of California Irvine, Irvine, CA 92697-7550, USA ; Department of Epidemiology, Institute for Public Health Genetics, University of Washington, Seattle, WA 98115, USA.
Stephanie A SantoricoDepartment of Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80217-3364, USA.

Funding

GENETIC ANALYSIS OF COMMON DISEASES: AN EVALUATIONR01GM031575 · NIGMS · UNIVERSITY OF TEXAS RIO GRANDE VALLEY · PI ALMASY, LAURA A. · 1985 to 2016
$7.8M
Identification of Issues and Expectations of Subjects Participating in Genetic StR01CA149051 · NCI · UNIVERSITY OF WASHINGTON · PI EDWARDS, KAREN L · 2011 to 2013
$1.2M
NCI NIH HHS R01 CA149051NIGMS NIH HHS R01 GM031575
6 · The paper itself

Abstract

Admixture mapping and association testing have been successfully applied to the detection of genes for complex diseases. Methods have also been developed to combine these approaches. As an initial step to determine the feasibility of combining admixture and association mapping in the context of whole genome sequencing, we have applied several methods to data from the Genetic Analysis Workshop 18. Here, we describe the steps necessary to carry out such a study from selection of reference populations and preprocessing of data through to the testing itself. We detected one significant result with a Bonferroni corrected p-value of 0.032 at single nucleotide polymorphism rs12639065. Computing local ancestry for Hispanic populations was challenging because there are relatively few methods by which to handle 3-way admixture, and publicly available Native American reference panels are scarce. However, combining admixture and association is a promising approach for detection of quantitative trait loci because it might be able to elevate the power of detection by combining 2 different sources of genetic signal.

Identifiers

PMID25519335
PMCPMC4143673

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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.