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Application de l'Analyse en Composantes Principales pour étudier l'adaptation biologique en génomique des populations

Abstract : Identifying genes involved in local adaptation is of major interest in population genetics. Current statistical methods for genome scans are no longer suited to the analysis of Next Generation Sequencing (NGS) data. We propose new statistical methods to perform genome scans on massive datasets. Our methods rely exclusively on Principal Component Analysis which use in population genetics will be discussed extensively. We also explain the reasons why our approaches can be seen as extensions of existing methods and demonstrate how our PCA-based statistics compare with state-of-the-art methods. Our work has led to the development of pcadapt, an R package designed for outlier detection for various genetic data.
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https://tel.archives-ouvertes.fr/tel-01758156
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Submitted on : Wednesday, April 4, 2018 - 11:36:08 AM
Last modification on : Wednesday, October 7, 2020 - 1:20:04 PM

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Keurcien Luu. Application de l'Analyse en Composantes Principales pour étudier l'adaptation biologique en génomique des populations. Bio-informatique [q-bio.QM]. Université Grenoble Alpes, 2017. Français. ⟨NNT : 2017GREAS053⟩. ⟨tel-01758156⟩

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