Evidence map›Paper›PMID 19799600›Full record

ArticleAnnals of human genetics2010

Variable selection method for quantitative trait analysis based on parallel genetic algorithm.

Siuli Mukhopadhyay, Varghese George, Hongyan Xu

Abstract read
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Article in Annals of human genetics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing 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

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Siuli MukhopadhyayDepartment of Mathematics, Indian Institute of Technology Bombay, Powai, Mumbai, India.
Varghese George
Hongyan Xu

Funding

GENETIC ANALYSIS OF COMMON DISEASES: AN EVALUATIONR01GM031575 · NIGMS · UNIVERSITY OF TEXAS RIO GRANDE VALLEY · PI ALMASY, LAURA A. · 1985 to 2016
$7.8M
NARAC The Genetics of Rheumatoid ArthritisR01AR044422 · NIAMS · NORTH SHORE UNIVERSITY HOSPITAL · PI GREGERSEN, PETER K. · 1997 to 2011
$6.0M
Association study of stroke risk in an admixed population of African AmericansR21NS057506 · NINDS · AUGUSTA UNIVERSITY · PI XU, HONGYAN · 2008 to 2009
$257k
NIAMS NIH HHS AR44422NIAMS NIH HHS R01 AR044422NIGMS NIH HHS GM031575NIGMS NIH HHS R01 GM031575NINDS NIH HHS R21 NS057506NINDS NIH HHS R21NS057506
6 · The paper itself

Abstract

Selection of important genetic and environmental factors is of strong interest in quantitative trait analyses. In this study, we use parallel genetic algorithm (PGA) to identify genetic and environmental factors in genetic association studies of complex human diseases. Our method can take account of both multiple markers across the genome and environmental factors, and also can be used to do fine mapping based on the results of haplotype analysis to select the markers that are associated with the quantitative traits. Using both simulated and real examples, we show that PGA is able to choose the variables correctly and is also an easy-to-use variable selection tool.

Indexed as

AlgorithmsModels, StatisticalQuantitative Trait, HeritableGenetic Association StudiesGenetic MarkersHumansModels, GeneticGenetic Markers

Identifiers

PMID19799600
PMCPMC2804783

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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.