Evidence map›Paper›PMID 19153260›Full record

ArticleGenetics2009

Selective genotyping and phenotyping strategies in a complex trait context.

Saunak Sen, Frank Johannes, Karl W Broman

Abstract readEvaluation Study
In one paragraph

Article in Genetics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 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.

Saunak SenDepartment of Epidemiology and Biostatistics, University of California, San Francisco, CA 94143-0560, USA. sen@biostat.ucsf.edu
Frank Johannes
Karl W Broman

Funding

Statistical Methods and Software for QTL MappingR01GM074244 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI BROMAN, KARL W · 2005 to 2013
$2.3M
Statistical Methods for Experimental Genome PopulationsR01GM078338 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI SEN, SAUNAK · 2007 to 2011
$1.1M
NIGMS NIH HHS GM074244NIGMS NIH HHS GM078338NIGMS NIH HHS R01 GM074244NIGMS NIH HHS R01 GM078338
6 · The paper itself

Abstract

Selective genotyping and phenotyping strategies are used to lower the cost of quantitative trait locus studies. Their efficiency has been studied primarily in simplified contexts--when a single locus contributes to the phenotype, and when the residual error (phenotype conditional on the genotype) is normally distributed. It is unclear how these strategies will perform in the context of complex traits where multiple loci, possibly linked or epistatic, may contribute to the trait. We also do not know what genotyping strategies should be used for nonnormally distributed phenotypes. For time-to-event phenotypes there is the additional question of choosing follow-up time duration. We use an information perspective to examine these experimental design issues in the broader context of complex traits and make recommendations on their use.

Indexed as

Quantitative Trait LociAnimalsChromosome MappingCrosses, GeneticEpistasis, GeneticFollow-Up StudiesGenetics, PopulationGenotypeHumansPhenotypePolymorphism, Single NucleotideResearch DesignSelection, Genetic

Identifiers

PMID19153260
PMCPMC2666524

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.