Evidence map›Paper›PMID 19416941›Full record

ArticleGenetics2009

Binary trait mapping in experimental crosses with selective genotyping.

Ani Manichaikul, Karl W Broman

Abstract read
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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Using visual scores for genomic prediction of complex traits in breeding programs.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023
    Article
  2. A maximum likelihood approach to functional mapping of longitudinal binary traits.Statistical applications in genetics and molecular biology · 2012
    Article
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

2 authors.

Ani ManichaikulDepartment of Biomedical Engineering, Univeristy of Virginia, Charlottesville, Virginia 22908, USA. amanicha@virginia.edu
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
NIGMS NIH HHS GM074244NIGMS NIH HHS R01 GM074244
6 · The paper itself

Abstract

Selective genotyping is an efficient strategy for mapping quantitative trait loci. For binary traits, where there are only two distinct phenotypic values (e.g., affected/unaffected or present/absent), one may consider selective genotyping of affected individuals, while genotyping none or only some of the unaffected. If selective genotyping of this sort is employed, the usual method for binary trait mapping, which considers phenotypes conditional on genotypes, cannot be used. We present an alternative approach, instead considering genotypes conditional on phenotypes, and compare this to the more standard method of analysis, both analytically and by example. For studies of rare binary phenotypes, we recommend performing an initial genome scan with all affected individuals and an equal number of unaffected, followed by genotyping the full cross in genomic regions of interest to confirm results from the initial screen.

Indexed as

AlgorithmsModels, GeneticAnimalsChromosome MappingCrosses, GeneticFemaleGenomeGenotypeLikelihood FunctionsLod ScoreMalePhenotype

Identifiers

PMID19416941
PMCPMC2710165

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.