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RNA-seq transcript quantification from reduced-representation data in recount2

View ORCID ProfileJack M. Fu, Kai Kammers, Abhinav Nellore, Leonardo Collado-Torres, Jeffrey T. Leek, Margaret A. Taub
doi: https://doi.org/10.1101/247346
Jack M. Fu
1Department of Biostatistics, Johns Hopkins University, Baltimore MD, USA
2Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA
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  • ORCID record for Jack M. Fu
Kai Kammers
2Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA
3Division of Biostatistics and Bioinformatics, Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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Abhinav Nellore
4Department of Biomedical Engineering, Oregon Health and Science University, Portland, OR, USA
5Department of Surgery, Oregon Health and Science University, Portland, OR, USA
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Leonardo Collado-Torres
2Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA
6Lieber Institute for Brain Development, Baltimore, MD, USA
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Jeffrey T. Leek
1Department of Biostatistics, Johns Hopkins University, Baltimore MD, USA
2Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA
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  • For correspondence: mtaub@jhsph.edu jtleek@gmail.com
Margaret A. Taub
1Department of Biostatistics, Johns Hopkins University, Baltimore MD, USA
2Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA
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  • For correspondence: mtaub@jhsph.edu jtleek@gmail.com
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Abstract

More than 70,000 short-read RNA-sequencing samples are publicly available through the recount2 project, a curated database of summary coverage data. However, no current methods can be directly applied to the reduced-representation information stored in this database to estimate transcript-level abundances. Here we present a linear model taking as input summary coverage of junctions and subdivided exons to output estimated abundances and associated uncertainty. We evaluate the performance of our model on simulated and real data, and provide a procedure to construct confidence intervals for estimates.

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Posted May 25, 2018.
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RNA-seq transcript quantification from reduced-representation data in recount2
Jack M. Fu, Kai Kammers, Abhinav Nellore, Leonardo Collado-Torres, Jeffrey T. Leek, Margaret A. Taub
bioRxiv 247346; doi: https://doi.org/10.1101/247346
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RNA-seq transcript quantification from reduced-representation data in recount2
Jack M. Fu, Kai Kammers, Abhinav Nellore, Leonardo Collado-Torres, Jeffrey T. Leek, Margaret A. Taub
bioRxiv 247346; doi: https://doi.org/10.1101/247346

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