Evidence map›Paper›PMID 18000014›Full record

ArticleDNA research : an international journal for rapid publication of reports on genes and genomes2007

Genotype matrix mapping: searching for quantitative trait loci interactions in genetic variation in complex traits.

Sachiko Isobe, Akihiro Nakaya, Satoshi Tabata

Abstract read
In one paragraph

Article in DNA research : an international journal for rapid publication of reports on genes and genomes, 2007. 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

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3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

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  15. Mapping candidate QTLs related to plant persistency in red clover.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2010
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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.

Sachiko Isobe1 National Agricultural Research Center for Hokkaido Region, Histujigaoka 1, Toyohira, Sapporo 062-8555, Japan. sisobe@kazusa.or.jp
Akihiro Nakaya
Satoshi Tabata

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In order to reveal quantitative trait loci (QTL) interactions and the relationship between various interactions in complex traits, we have developed a new QTL mapping approach, named genotype matrix mapping (GMM), which searches for QTL interactions in genetic variation. The central approach in GMM is the following. (1) Each tested marker is given a virtual matrix, named a genotype matrix (GM), containing intersecting lines and rows equal to the total allele number for that marker in the population analyzed. (2) QTL interactions are then estimated and compared through virtual networks among the GMs. To evaluate the contribution of marker combinations to a quantitative phenotype, the GMM method divides the samples into two non-overlapping subclasses, S(0) and S(1); the former contains the samples that have a specific genotype pattern to be evaluated, and the latter contains samples that do not. Based on this division, the F-measure is calculated as an index of significance. With the GMM method, we extracted significant marker combinations consisting of one to three interacting markers. The results indicated there were multiple QTL interactions affecting the phenotype (flowering date). GMM will be a valuable approach to identify QTL interactions in genetic variation of a complex trait within a variety of organisms.

Indexed as

Genetic VariationQuantitative Trait LociAlgorithmsAllelesChromosome MappingDatabases, GeneticFlowersGenetic MarkersGenotypeModels, GeneticPhenotypeTrifoliumGenetic Markers

Identifiers

PMID18000014
PMCPMC2779902

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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.