Evidence map›Paper›PMID 19216798›Full record

ArticleBioData mining2009

Database mining for selection of SNP markers useful in admixture mapping.

Tesfaye M Baye, Hemant K Tiwari, David B Allison, Rodney C Go

Abstract read
In one paragraph

Article in BioData mining, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

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  7. Tracking the origins of Yakutian horses and the genetic basis for their fast adaptation to subarctic environments.Proceedings of the National Academy of Sciences of the United States of America · 2015
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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

4 authors.

Tesfaye M BayeHuman and Molecular Genetics Center, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA. tmersha@mcw.edu
Hemant K Tiwari
David B Allison
Rodney C Go

Funding

Why is the prevalence of obesity so high in U.S. Southern States? Regional predictors of BMI and obesity treatment response.P30DK056336 · NIDDK · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI James O Hill · 2000 to 2026
$31.9M
The molecular genetic analysis of human obesityR01DK052431 · NIDDK · ROCKEFELLER UNIVERSITY · PI CHUNG, WENDY K, LEIBEL, RUDOLPH L · 1996 to 2020
$11.6M
Schizophrenia Liability Genes among African AmericansR01MH066181 · NIMH · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI GO, RODNEY CHUN PUNG · 2002 to 2006
$4.7M
Genome-wide Structured Association Testing & Regional Admixture MappingR01GM077490 · NIGMS · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI LIU, NIANJUN · 2007 to 2010
$1.1M
Search for AD Genes in the NIMH Sibling DatasetR01NS045934 · NINDS · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI GO, RODNEY CHUN PUNG · 2002 to 2004
$981k
Multiple Imputation in Genetic StudiesR21LM008791 · NLM · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI TIWARI, HEMANT K. · 2007 to 2008
$280k
NIDDK NIH HHS P30 DK056336NIDDK NIH HHS R01 DK052431NIGMS NIH HHS R01 GM077490NIMH NIH HHS R01 MH066181NINDS NIH HHS R01 NS045934NLM NIH HHS R21 LM008791
6 · The paper itself

Abstract

backgroundNew technologies make it possible for the first time to genotype hundreds of thousands of SNPs simultaneously. A wealth of genomic information in the form of publicly available databases is underutilized as a potential resource for uncovering functionally relevant markers underlying complex human traits. Given the huge amount of SNP data available from the annotation of human genetic variation, data mining is a reasonable approach to investigating the number of SNPs that are informative for ancestry information.

methodsThe distribution and density of SNPs across the genome of African and European populations were extensively investigated by using the HapMap, Affymetrix, and Illumina SNP databases. We exploited these resources by mining the data available from each of these databases to prioritize potential candidate SNPs useful for admixture mapping in complex human diseases and traits. Over 4 million SNPs were compared between Africans and Europeans on the basis of a pre-specified recommended allele frequency difference (delta) value of >or= 0.3.

resultsThe method identified 15% of HapMap, 11% of Affymetrix, and 14% of Illumina SNP sets as candidate SNPs, termed ancestry informative markers (AIMs). These AIM panels with assigned rs numbers, allele frequencies in each ethnic group, delta value, and map positions are all posted on our website http://www.ssg.uab.edu/downloads/admixture_mapping/SNPAIMs.txt. All marker information in this data set is freely and publicly available without restriction.

conclusionThe selected SNP sets represent valuable resources for admixture mapping studies. The overlap between selected AIMs by this single measure of marker informativeness in the different platforms is discussed.

Identifiers

PMID19216798
PMCPMC2649128

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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.