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A method to reconstruct the native TCRαβ from single cell RNA-seq data of Ag-specific T cells and then to link these with the gene expression profile of individual cells. The workflow allows transcript quantification, noise reduction, gene variability analysis, differential expression, co-expression analysis, and finally reconstruction of the full TCRαβ transcripts. We demonstrate that single-cell transcriptome analysis can successfully distinguish Ag-specific T cell populations sorted directly from resting memory cells in peripheral blood and sorted after ex vivo stimulation. This approach allows a detailed analysis of the TCR diversity and its relationship with the transcriptional profile of different clones.

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TopHat2, Trinity, Ensembl GRCh37, MiGMAP
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VDJPuzzle support



  • Fabio Luciani < >


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Systems Medicine in Infectious Diseases, Inflammation and Infection Research Centre, School of Medical Sciences, UNSW, Sydney, Australia; Kirby Institute for Infection and Immunity, UNSW, Sydney, Australia; Department of Microbiology and Immunology, University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia

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