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Modelling capture efficiency of single cell RNA-sequencing data improves inference of transcriptome-wide burst kinetics
View ORCID ProfileWenhao Tang, View ORCID ProfileAndreas Christ Sølvsten Jørgensen, View ORCID ProfileSamuel Marguerat, View ORCID ProfilePhilipp Thomas, View ORCID ProfileVahid Shahrezaei
doi: https://doi.org/10.1101/2023.03.06.531327
Wenhao Tang
1Department of Mathematics, Faculty of Natural Sciences, Imperial College London, London, UK
Andreas Christ Sølvsten Jørgensen
1Department of Mathematics, Faculty of Natural Sciences, Imperial College London, London, UK
Samuel Marguerat
2MRC London Institute of Medical Sciences, London, United Kingdom
3Institute of Clinical Sciences, Imperial College London, London, United Kingdom
4UCL Cancer Institute, University College London, London WC1E 6DD, United Kingdom
Philipp Thomas
1Department of Mathematics, Faculty of Natural Sciences, Imperial College London, London, UK
Vahid Shahrezaei
1Department of Mathematics, Faculty of Natural Sciences, Imperial College London, London, UK

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Posted March 07, 2023.
Modelling capture efficiency of single cell RNA-sequencing data improves inference of transcriptome-wide burst kinetics
Wenhao Tang, Andreas Christ Sølvsten Jørgensen, Samuel Marguerat, Philipp Thomas, Vahid Shahrezaei
bioRxiv 2023.03.06.531327; doi: https://doi.org/10.1101/2023.03.06.531327
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