Evidence map›Paper›PMID 34149806›Full record

ArticleFrontiers in genetics2021

Genomic Prediction of Average Daily Gain, Back-Fat Thickness, and Loin Muscle Depth Using Different Genomic Tools in Canadian Swine Populations.

Siavash Salek Ardestani, Mohsen Jafarikia, Mehdi Sargolzaei, Brian Sullivan, Younes Miar

Abstract read
In one paragraph

Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
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  7. The ovineFrontiers in veterinary science · 2023
    Article
  8. Article
  9. Accuracy of genomic prediction of maternal traits in pigs using Bayesian variable selection methods.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2022
    Article
  10. 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

5 authors.

Siavash Salek ArdestaniDepartment of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada.
Mohsen JafarikiaCanadian Centre for Swine Improvement, Ottawa, ON, Canada.
Mehdi SargolzaeiDepartment of Pathobiology, University of Guelph, Guelph, ON, Canada.
Brian SullivanCanadian Centre for Swine Improvement, Ottawa, ON, Canada.
Younes MiarDepartment of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Improvement of prediction accuracy of estimated breeding values (EBVs) can lead to increased profitability for swine breeding companies. This study was performed to compare the accuracy of different popular genomic prediction methods and traditional best linear unbiased prediction (BLUP) for future performance of back-fat thickness (BFT), average daily gain (ADG), and loin muscle depth (LMD) in Canadian Duroc, Landrace, and Yorkshire swine breeds. In this study, 17,019 pigs were genotyped using Illumina 60K and Affymetrix 50K panels. After quality control and imputation steps, a total of 41,304, 48,580, and 49,102 single-nucleotide polymorphisms remained for Duroc (

Indexed as

BayesCGBLUPgenomic predictionsingle-step GBLUPswine

Identifiers

PMID34149806
PMCPMC8209496

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.