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Longitudinal high-throughput TCR repertoire profiling reveals the dynamics of T cell memory formation after mild COVID-19 infection

Anastasia A. Minervina; Ekaterina A. Komech; Aleksei Titov; Meriem Bensouda Koraichi; Elisa Rosati; Ilgar Z. Mamedov; Andre Franke; Grigory A. Efimov; Dmitriy M. Chudakov; Thierry Mora; Aleksandra M. Walczak; Yury B. Lebedev; Mikhail V. Pogorelyy


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    <dcat:keyword>TCR</dcat:keyword>
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    <dct:description>&lt;p&gt;Processed TCRbeta and TCRalpha repertoires after mild COVID-19 infection,&amp;nbsp;see&amp;nbsp;preprint:&amp;nbsp;&lt;a href="https://www.biorxiv.org/content/10.1101/2020.05.18.100545v1"&gt;https://www.biorxiv.org/content/10.1101/2020.05.18.100545v1&lt;/a&gt;&lt;/p&gt; &lt;p&gt;and GitHub repository:&amp;nbsp;&lt;a href="https://github.com/pogorely/Minervina_COVID"&gt;https://github.com/pogorely/Minervina_COVID&lt;/a&gt;&lt;/p&gt; &lt;p&gt;Two donors (M and W), two biological replicates of PBMC&amp;nbsp;(F1 and F2), CD4+, CD8+, and Memory subpopulations&amp;nbsp;for each post-infection time points (day 15, 30, 37, 45 post-infection), and pre-infection PBMC repertoires sampled in 2019 and 2018.&amp;nbsp;&lt;/p&gt;</dct:description>
    <dct:description xml:lang="">Demultiplexing and UMI-consenuses were done with migec (v. 1.2.7), alignments and assembly of UMI-consensuses into clonotypes performed with mixcr (v. 2.1.11).</dct:description>
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