Evidence map›Paper›PMID 18513279›Full record

ArticleAnnals of human genetics2008

Using population mixtures to optimize the utility of genomic databases: linkage disequilibrium and association study design in India.

T J Pemberton, M Jakobsson, D F Conrad, G Coop, J D Wall, J K Pritchard, P I Patel, N A Rosenberg

Abstract read
In one paragraph

Article in Annals of human genetics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed.

  1. Article
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  4. Article
  5. Article
  6. Designing genetic association studies for complex traits in India.The Indian journal of medical research · 2017
    Article
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  18. Review
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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

8 authors.

T J PembertonInstitute for Genetic Medicine, University of Southern California, 2250 Alcazar St., Los Angeles, California 90033, USA.
M Jakobsson
D F Conrad
G Coop
J D Wall
J K Pritchard
P I Patel
N A Rosenberg

Funding

Population-Genetic Studies for Association MappingR01GM081441 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ROSENBERG, NOAH · 2007 to 2011
$1.7M
EXTRAMURAL RESEARCH FACILITIES CONTRUCTION PROJECTC06CA062528 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI KEDES, LAURENCE H · 1993 to 1994
–
EXTRAMURAL RESEARCH FACILITIES CONSTRUCTIONC06RR010600 · NCRR · UNIVERSITY OF SOUTHERN CALIFORNIA · PI KEDES, LAURENCE H · 1994 to 1994
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RESEARCH FACILITIES IMPROVEMENT PROGRAM AND REMODELINGC06RR014514 · NCRR · UNIVERSITY OF SOUTHERN CALIFORNIA · PI KEDES, LAURENCE H · 1999 to 1999
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NCI NIH HHS C06 CA062528NCI NIH HHS CA62528-01NCRR NIH HHS C06 RR014514NCRR NIH HHS RR10600-01NCRR NIH HHS RR14514-01NIGMS NIH HHS GM081441NIGMS NIH HHS R01 GM081441
6 · The paper itself

Abstract

When performing association studies in populations that have not been the focus of large-scale investigations of haplotype variation, it is often helpful to rely on genomic databases in other populations for study design and analysis - such as in the selection of tag SNPs and in the imputation of missing genotypes. One way of improving the use of these databases is to rely on a mixture of database samples that is similar to the population of interest, rather than using the single most similar database sample. We demonstrate the effectiveness of the mixture approach in the application of African, European, and East Asian HapMap samples for tag SNP selection in populations from India, a genetically intermediate region underrepresented in genomic studies of haplotype variation.

Indexed as

Databases, GeneticLinkage DisequilibriumGenetics, PopulationGenome, HumanHaplotypesHumansIndiaPolymorphism, Single NucleotidePopulation GroupsResearch Design

Identifiers

PMID18513279
PMCPMC2495051

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.