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Dataset . 2023
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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Prunus armeniaca SNPs dataset

Authors: Gargiulo, Roberta; Heuertz, Myriam; Decroocq, Véronique;

Prunus armeniaca SNPs dataset

Abstract

-"armeniaca.SNPs.vcf.gz": dataset including SNPs genotypes for 255 individuals of Prunus armeniaca from Central Asia, filtered from Groppi et al. 2021 (https://www.nature.com/articles/s41467-021-24283-6). -"P.armeniaca Q-values.xlsx": fastStructure Q-value assignment as obtained in Groppi et al. (2021) for each individual (indicated by unique labels in the first column). Q-value assignments to the two main Asian gene pools ("Northern" and "Southern" gene pools). This dataset was prepared in association with the manuscript: Gargiulo R., Decroocq V., González-Martínez S.C., Paz-Vinas I., Aury J-M., Lesur Kupin I., Plomion C., Schmitt S., Scotti I., Heuertz M. 2023. Estimation of contemporary effective population size in plant populations: limitations of genomic datasets. bioRxiv 2023.07.18.549323; doi: https://doi.org/10.1101/2023.07.18.549323 See the analytical workflow at: https://github.com/Ralpina/Ne-plant-genomic-datasets/blob/main/README.md (https://doi.org/10.5281/zenodo.8134169)

{"references": ["Groppi, Alexis et al. (2021). Population genomics of apricots unravels domestication history and adaptive events. Nature Communications. 12, 3956.", "Gargiulo R.,\u00a0Decroocq V.,\u00a0Gonz\u00e1lez-Mart\u00ednez S.C., Paz-Vinas I.,\u00a0Aury J-M., Lesur Kupin I., Plomion C., Schmitt S., Scotti I., Heuertz M. (2023). Estimation of contemporary effective population size in plant populations: limitations of genomic datasets.\u00a0bioRxiv\u00a02023.07.18.549323;\u00a0doi:\u00a0https://doi.org/10.1101/2023.07.18.549323", "Gargiulo R. (2023). Ralpina/Ne-plant-genomic-datasets: Ne-plant-genomic-datasets (v1.0.0). Zenodo. https://doi.org/10.5281/zenodo.8134169"]}

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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