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Rail-RNA: Scalable analysis of RNA-seq splicing and coverage
Abhinav Nellore, Leonardo Collado-Torres, Andrew E. Jaffe, José Alquicira-Hernández, Jacob Pritt, James Morton, Jeffrey T. Leek, Ben Langmead
doi: https://doi.org/10.1101/019067
Abhinav Nellore
1Department of Computer Science, Johns Hopkins University
2Department of Biostatistics, Johns Hopkins University
3Center for Computational Biology, Johns Hopkins University
Leonardo Collado-Torres
2Department of Biostatistics, Johns Hopkins University
3Center for Computational Biology, Johns Hopkins University
4Lieber Institute for Brain Development, Johns Hopkins Medical Campus
Andrew E. Jaffe
2Department of Biostatistics, Johns Hopkins University
3Center for Computational Biology, Johns Hopkins University
4Lieber Institute for Brain Development, Johns Hopkins Medical Campus
5Department of Mental Health, Johns Hopkins University
José Alquicira-Hernández
2Department of Biostatistics, Johns Hopkins University
6Undergraduate Program on Genomic Sciences, National Autonomous University of Mexico
Jacob Pritt
1Department of Computer Science, Johns Hopkins University
3Center for Computational Biology, Johns Hopkins University
James Morton
7Department of Computer Science, University of Colorado Boulder
Jeffrey T. Leek
2Department of Biostatistics, Johns Hopkins University
3Center for Computational Biology, Johns Hopkins University
Ben Langmead
1Department of Computer Science, Johns Hopkins University
2Department of Biostatistics, Johns Hopkins University
3Center for Computational Biology, Johns Hopkins University

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Posted August 12, 2015.
Rail-RNA: Scalable analysis of RNA-seq splicing and coverage
Abhinav Nellore, Leonardo Collado-Torres, Andrew E. Jaffe, José Alquicira-Hernández, Jacob Pritt, James Morton, Jeffrey T. Leek, Ben Langmead
bioRxiv 019067; doi: https://doi.org/10.1101/019067
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