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Accounting for fragments of unexpected origin improves transcript quantification in RNA-seq simulations focused on increased realism

View ORCID ProfileAvi Srivastava, View ORCID ProfileMohsen Zakeri, View ORCID ProfileHirak Sarkar, View ORCID ProfileCharlotte Soneson, View ORCID ProfileCarl Kingsford, View ORCID ProfileRob Patro
doi: https://doi.org/10.1101/2021.01.17.426996
Avi Srivastava
1New York Genome Center and NYU Center for Genomics and Systems Biology, New York City, NY, USA
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Mohsen Zakeri
2Department of Computer Science and Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA
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Hirak Sarkar
3Harvard Medical School, Boston, Massachusetts, USA
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Charlotte Soneson
4Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
5SIB Swiss Institute of Bioinformatics, Basel, Switzerland
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Carl Kingsford
6Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
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  • For correspondence: carlk@cs.cmu.edu rob@cs.umd.edu
Rob Patro
2Department of Computer Science and Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA
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  • For correspondence: carlk@cs.cmu.edu rob@cs.umd.edu
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Posted January 19, 2021.
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Accounting for fragments of unexpected origin improves transcript quantification in RNA-seq simulations focused on increased realism
Avi Srivastava, Mohsen Zakeri, Hirak Sarkar, Charlotte Soneson, Carl Kingsford, Rob Patro
bioRxiv 2021.01.17.426996; doi: https://doi.org/10.1101/2021.01.17.426996
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Accounting for fragments of unexpected origin improves transcript quantification in RNA-seq simulations focused on increased realism
Avi Srivastava, Mohsen Zakeri, Hirak Sarkar, Charlotte Soneson, Carl Kingsford, Rob Patro
bioRxiv 2021.01.17.426996; doi: https://doi.org/10.1101/2021.01.17.426996

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