Evidence map›Paper›PMID 12811538›Full record

ArticleHuman genetics2003

Comparison of strategies for selecting single nucleotide polymorphisms for case/control association studies.

Qiqing Huang, Yun-Xin Fu, Eric Boerwinkle

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in Human genetics, 2003. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Association betweenArchives animal breeding · 2019
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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.

Qiqing HuangHuman Genetics Center, University of Texas-Houston Health Science Center, 1200 Herman Pressler, Suite 453E, Houston, TX 77030, USA.
Yun-Xin Fu
Eric Boerwinkle

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It is widely believed that a subset of single nucleotide polymorphisms (SNPs) is able to capture the majority of the information for genotype-phenotype association studies that is contained in the complete compliment of genetic variations. The question remains, how does one select that particular subset of SNPs in order to maximize the power of detecting a significant association? In this study, we have used a simulation approach to compare three competing methods of site selection: random selection, selection based on pair-wise linkage disequilibrium, and selection based on maximizing haplotype diversity. The results indicate that site selection based on maximizing haplotype diversity is preferred over random selection and selection based on pair-wise linkage disequilibrium. The results also indicate that it is more prudent to increase the sample size to improve a study's power than to continuously increase the number of SNPs. These results have direct implications for designing gene-based and genome-wide association studies.

Indexed as

Case-Control StudiesPatient SelectionPolymorphism, Single NucleotideSample SizeHaplotypesHumansLinkage DisequilibriumPhenotypeRegression Analysis

Identifiers

What OpenQuestion holds

Textmetadata
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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.