ArticleFrontiers in genetics2019
Selection of Optimal Ancestry Informative Markers for Classification and Ancestry Proportion Estimation in Pigs.
Article in Frontiers in genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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.
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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.
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Who cites it
7 citing papers in PubMed, 9 citations in OpenAlex.
- Article
- Evaluation of the Breed Composition of Pork via Population Structure Analysis in Pigs.Animals : an open access journal from MDPI · 2024Article
- snpAIMeR: R package for evaluating ancestry informative marker contributions in non-model population diagnostics.Bioinformatics (Oxford, England) · 2024Article
- Recapitulating whole genome based population genetic structure for Indian wild tigers through an ancestry informative marker panel.Heredity · 2022Article
- Genetic ancestry plays a central role in population pharmacogenomics.Communications biology · 2021Article
- Improving read alignment through the generation of alternative reference via iterative strategy.Scientific reports · 2020Article
- Identification of Ancestry Informative Marker (AIM) Panels to Assess Hybridisation between Feral and Domestic Sheep.Animals : an open access journal from MDPI · 2020Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Using small sets of ancestry informative markers (AIMs) constitutes a cost-effective method to accurately estimate the ancestry proportions of individuals. This study aimed to generate a small and effective number of AIMs from ∼60 K single nucleotide polymorphism (SNP) data of porcine and estimate three ancestry proportions [East China pig (ECHP), South China pig (SCHP), and European commercial pig (EUCP)] from Asian breeds and European domestic breeds. A total of 186 samples of 10 pure breeds were divided into three groups: ECHP, SCHP, and EUCP. Using these samples and a one-vs.-rest SVM classifier, we found that using only seven AIMs could completely separate the three groups. Subsequently, we utilized supervised ADMIXTURE to calculate ancestry proportions and found that the 129 AIMs performed well on ancestry estimates when pseudo admixed individuals were used. Furthermore, another 969 samples of 61 populations were applied to evaluate the performance of the 129 AIMs. We also observed that the 129 AIMs were highly correlated with estimates using ∼60 K SNP data for three ancestry components: ECHP (Pearson correlation coefficient (
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