Evidence map›Paper›PMID 30045858›Full record

ArticleGenetics2018

Accurate Genotype Imputation in Multiparental Populations from Low-Coverage Sequence.

Chaozhi Zheng, Martin P Boer, Fred A van Eeuwijk

Open access · bronzeAbstract read
In one paragraph

Article in Genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
3.6field-weighted citation impact, top 7% of its field
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

22 citing papers in PubMed, 43 citations in OpenAlex.

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  4. Genotyping of SNPs in bread wheat at reduced cost from pooled experiments and imputation.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024
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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 at 1 institution in 1 country.

Chaozhi ZhengBiometris, Wageningen University and Research, Wageningen, The Netherlands chaozhi.zheng@wur.nl.ORCID 0000-0001-6030-3933
Martin P BoerBiometris, Wageningen University and Research, Wageningen, The Netherlands.
Fred A van EeuwijkBiometris, Wageningen University and Research, Wageningen, The Netherlands.
Wageningen University & Research · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many different types of multiparental populations have recently been produced to increase genetic diversity and resolution in QTL mapping. Low-coverage, genotyping-by-sequencing (GBS) technology has become a cost-effective tool in these populations, despite large amounts of missing data in offspring and founders. In this work, we present a general statistical framework for genotype imputation in such experimental crosses from low-coverage GBS data. Generalizing a previously developed hidden Markov model for calculating ancestral origins of offspring DNA, we present an imputation algorithm that does not require parental data and that is applicable to bi- and multiparental populations. Our imputation algorithm allows heterozygosity of parents and offspring as well as error correction in observed genotypes. Further, our approach can combine imputation and genotype calling from sequencing reads, and it also applies to called genotypes from SNP array data. We evaluate our imputation algorithm by simulated and real data sets in four different types of populations: the F

Indexed as

AlgorithmsChromosome MappingGenome-Wide Association StudyGenomicsGenotypeGenotyping TechniquesModels, GeneticQuantitative Trait LociSequence Analysis, DNAcross-pollinated (CP) populationgenotype imputationgenotyping by sequencinghidden Markov modelMPPMultiparent Advanced Generation Inter-Cross (MAGIC)multiparental populations

Identifiers

PMID30045858
PMCPMC6116951
OpenAlexW2883011667

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.