Evidence map›Paper›PMID 27921120›Full record

ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2017

The potential of probabilistic graphical models in linkage map construction.

Huange Wang, Fred A van Eeuwijk, Johannes Jansen

Abstract read
In one paragraph

Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 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.

Huange WangBiometris, Wageningen University and Research Centre, P.O. Box 16, 6700 AA, Wageningen, The Netherlands. huan20042004@gmail.com.ORCID http://orcid.org/0000-0002-9216-2749
Fred A van EeuwijkBiometris, Wageningen University and Research Centre, P.O. Box 16, 6700 AA, Wageningen, The Netherlands.
Johannes JansenBiometris, Wageningen University and Research Centre, P.O. Box 16, 6700 AA, Wageningen, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

key messageProbabilistic graphical models show great potential for robust and reliable construction of linkage maps. We show how to use probabilistic graphical models to construct high-quality linkage maps in the face of data perturbations caused by genotyping errors and reciprocal translocations. It has been shown that linkage map construction can be hampered by the presence of genotyping errors and chromosomal rearrangements such as inversions and translocations. Here, we report a novel method for linkage map construction using probabilistic graphical models. The method is proven, both theoretically and practically, to be effective in filtering out markers that contain genotyping errors. In particular, it carries out marker filtering and ordering simultaneously, and is therefore superior to the standard post hoc filtering using nearest-neighbour stress. Furthermore, we demonstrate empirically that the proposed method offers a promising solution to linkage map construction in the case of a reciprocal translocation.

Indexed as

Chromosome MappingGenetic LinkageModels, GeneticModels, StatisticalAlgorithmsAllelesChromosome InversionChromosomes, PlantCucumis sativusGenotyping TechniquesHaplotypesHordeumPhenotypeTranslocation, Genetic

Identifiers

PMID27921120
PMCPMC5263214

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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.