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satuRn: Scalable Analysis of differential Transcript Usage for bulk and single-cell RNA-sequencing applications
View ORCID ProfileJeroen Gilis, View ORCID ProfileKristoffer Vitting-Seerup, View ORCID ProfileKoen Van den Berge, View ORCID ProfileLieven Clement
doi: https://doi.org/10.1101/2021.01.14.426636
Jeroen Gilis
1Department of Applied Mathematics, Computer Science & Statistics, Ghent University, Belgium
2Data Mining and Modeling for Biomedicine, VIB Center for Inflammation Research, Ghent, Belgium
6Bioinformatics Institute Ghent, Ghent University, Ghent, Belgium
Kristoffer Vitting-Seerup
3Department of Biology, The Bioinformatics Centre, University of Copenhagen
4Biotech Research and Innovation Centre (BRIC), University of Copenhagen
Koen Van den Berge
1Department of Applied Mathematics, Computer Science & Statistics, Ghent University, Belgium
5Department of Statistics, University of California, Berkeley, CA, USA
6Bioinformatics Institute Ghent, Ghent University, Ghent, Belgium
Lieven Clement
1Department of Applied Mathematics, Computer Science & Statistics, Ghent University, Belgium
6Bioinformatics Institute Ghent, Ghent University, Ghent, Belgium
Posted January 16, 2021.
satuRn: Scalable Analysis of differential Transcript Usage for bulk and single-cell RNA-sequencing applications
Jeroen Gilis, Kristoffer Vitting-Seerup, Koen Van den Berge, Lieven Clement
bioRxiv 2021.01.14.426636; doi: https://doi.org/10.1101/2021.01.14.426636
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