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Human splicing diversity across the Sequence Read Archive

Abhinav Nellore, Andrew E. Jaffe, Jean-Philippe Fortin, José Alquicira-Hernández, Leonardo Collado-Torres, Siruo Wang, Robert A. Phillips III, Nishika Karbhari, Kasper D. Hansen, Ben Langmead, Jeffrey T. Leek
doi: https://doi.org/10.1101/038224
Abhinav Nellore
1Department of Computer Science, Johns Hopkins University
2Department of Biostatistics, Johns Hopkins University
3Center for Computational Biology, Johns Hopkins University
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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
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Jean-Philippe Fortin
2Department of Biostatistics, Johns Hopkins University
3Center for Computational Biology, Johns Hopkins University
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José Alquicira-Hernández
2Department of Biostatistics, Johns Hopkins University
6Undergraduate Program on Genomic Sciences, National Autonomous University of Mexico
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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
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Siruo Wang
2Department of Biostatistics, Johns Hopkins University
7Department of Mathematics and Computer Science, Centre College
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Robert A. Phillips III
2Department of Biostatistics, Johns Hopkins University
8Department of Biological Sciences, Salisbury University
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Nishika Karbhari
2Department of Biostatistics, Johns Hopkins University
9Department of Biological Sciences, University of Texas at Austin
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Kasper D. Hansen
2Department of Biostatistics, Johns Hopkins University
3Center for Computational Biology, Johns Hopkins University
10McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University
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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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  • For correspondence: langmea@cs.jhu.edu
Jeffrey T. Leek
2Department of Biostatistics, Johns Hopkins University
3Center for Computational Biology, Johns Hopkins University
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  • For correspondence: langmea@cs.jhu.edu
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Abstract

We aligned 21,504 publicly available Illumina-sequenced human RNA-seq samples from the Sequence Read Archive (SRA) to the human genome and compared detected exon-exon junctions with junctions in several recent gene annotations. 56,865 junctions (18.6%) found in at least 1,000 samples were not annotated, and their expression associated with tissue type. Newer samples contributed few novel well-supported junctions, with 96.1% of junctions detected in at least 20 reads across samples present in samples before 2013. Junction data is compiled into a resource called intropolis available at http://intropolis.rail.bio. We discuss an application of this resource to cancer involving a recently validated isoform of the ALK gene.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted January 29, 2016.
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Human splicing diversity across the Sequence Read Archive
Abhinav Nellore, Andrew E. Jaffe, Jean-Philippe Fortin, José Alquicira-Hernández, Leonardo Collado-Torres, Siruo Wang, Robert A. Phillips III, Nishika Karbhari, Kasper D. Hansen, Ben Langmead, Jeffrey T. Leek
bioRxiv 038224; doi: https://doi.org/10.1101/038224
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Human splicing diversity across the Sequence Read Archive
Abhinav Nellore, Andrew E. Jaffe, Jean-Philippe Fortin, José Alquicira-Hernández, Leonardo Collado-Torres, Siruo Wang, Robert A. Phillips III, Nishika Karbhari, Kasper D. Hansen, Ben Langmead, Jeffrey T. Leek
bioRxiv 038224; doi: https://doi.org/10.1101/038224

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