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SUPPA: a super-fast pipeline for alternative splicing analysis from RNA-Seq

Gael P. Alamancos, Amadís Pagès, Juan L. Trincado, Nicolás Bellora, Eduardo Eyras
doi: https://doi.org/10.1101/008763
Gael P. Alamancos
1Computational Genomics, Universitat Pompeu Fabra, E08003, Barcelona, Spain
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Amadís Pagès
1Computational Genomics, Universitat Pompeu Fabra, E08003, Barcelona, Spain
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Juan L. Trincado
1Computational Genomics, Universitat Pompeu Fabra, E08003, Barcelona, Spain
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Nicolás Bellora
2INIBIOMA, CONICET-UNComahue, Bariloche, Río Negro, Argentina
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Eduardo Eyras
1Computational Genomics, Universitat Pompeu Fabra, E08003, Barcelona, Spain
3Catalan Institution for Research and Advanced Studies, E08010 Barcelona, Spain
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ABSTRACT

High-throughput RNA sequencing allows genome-wide analyses of pre-mRNA splicing across multiple conditions. However, the increasing number of available datasets represents a major challenge in terms of time and storage required for analyses. Here we describe SUPPA, a computational pipeline to calculate relative inclusion values of alternative splicing events, exploiting fast transcript quantification of a known annotation. SUPPA provides a fast and accurate approach to calculate inclusion levels of alternative splicing events from a large number of samples, thereby facilitating systematic analyses in the context of large-scale projects using limited computational resources. SUPPA is available at https://bitbucket.org/regulatorygenomicsupf/suppa under the MIT license and is implemented in Python 2.7.

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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 September 04, 2014.
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SUPPA: a super-fast pipeline for alternative splicing analysis from RNA-Seq
Gael P. Alamancos, Amadís Pagès, Juan L. Trincado, Nicolás Bellora, Eduardo Eyras
bioRxiv 008763; doi: https://doi.org/10.1101/008763
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SUPPA: a super-fast pipeline for alternative splicing analysis from RNA-Seq
Gael P. Alamancos, Amadís Pagès, Juan L. Trincado, Nicolás Bellora, Eduardo Eyras
bioRxiv 008763; doi: https://doi.org/10.1101/008763

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