Evidence map›Paper›PMID 27129452›Full record

ArticleMammalian genome : official journal of the International Mammalian Genome Society2016

Genotype imputation in the domestic dog.

S G Friedenberg, K M Meurs

Open access · greenAbstract read
In one paragraph

Article in Mammalian genome : official journal of the International Mammalian Genome Society, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
5.1field-weighted citation impact, top 5% 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

36 citing papers in PubMed, 52 citations in OpenAlex.

  1. Article
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  5. A NovelJournal of fungi (Basel, Switzerland) · 2024
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  6. GWAS using low-pass whole genome sequence reveals a novel locus in canine congenital idiopathic megaesophagus.Mammalian genome : official journal of the International Mammalian Genome Society · 2023
    Article
  7. Article
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  9. Best practices for analyzing imputed genotypes from low-pass sequencing in dogs.Mammalian genome : official journal of the International Mammalian Genome Society · 2022
    Article
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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

2 authors at 1 institution in 1 country.

S G FriedenbergDepartment of Clinical Sciences and Comparative Medicine Institute, North Carolina State University College of Veterinary Medicine, 1060 William Moore Drive, Raleigh, NC, 27607, USA. steven_friedenberg@ncsu.edu.
K M MeursDepartment of Clinical Sciences and Comparative Medicine Institute, North Carolina State University College of Veterinary Medicine, 1060 William Moore Drive, Raleigh, NC, 27607, USA.
North Carolina State University · US

Funding

Comparative Medicine and Translational Research Training ProgramT32OD011130 · OD · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI Lauren Virginia Schnabel · 2012 to 2026
$7.8M
NIH HHS T32 OD011130
6 · The paper itself

Abstract

Application of imputation methods to accurately predict a dense array of SNP genotypes in the dog could provide an important supplement to current analyses of array-based genotyping data. Here, we developed a reference panel of 4,885,283 SNPs in 83 dogs across 15 breeds using whole genome sequencing. We used this panel to predict the genotypes of 268 dogs across three breeds with 84,193 SNP array-derived genotypes as inputs. We then (1) performed breed clustering of the actual and imputed data; (2) evaluated several reference panel breed combinations to determine an optimal reference panel composition; and (3) compared the accuracy of two commonly used software algorithms (Beagle and IMPUTE2). Breed clustering was well preserved in the imputation process across eigenvalues representing 75 % of the variation in the imputed data. Using Beagle with a target panel from a single breed, genotype concordance was highest using a multi-breed reference panel (92.4 %) compared to a breed-specific reference panel (87.0 %) or a reference panel containing no breeds overlapping with the target panel (74.9 %). This finding was confirmed using target panels derived from two other breeds. Additionally, using the multi-breed reference panel, genotype concordance was slightly higher with IMPUTE2 (94.1 %) compared to Beagle; Pearson correlation coefficients were slightly higher for both software packages (0.946 for Beagle, 0.961 for IMPUTE2). Our findings demonstrate that genotype imputation from SNP array-derived data to whole genome-level genotypes is both feasible and accurate in the dog with appropriate breed overlap between the target and reference panels.

Indexed as

GenotypeAllelesAnimalsBreedingComputer SimulationDogsModels, GeneticPolymorphism, Single NucleotideSequence Analysis, DNA

Identifiers

PMID27129452
PMCPMC5002369
OpenAlexW2343555861

What OpenQuestion holds

Textmetadata
LicenceTDM
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.