Design of RNA splicing analysis null models for post hoc filtering of Drosophila head RNA-Seq data with the splicing analysis kit (Spanki)
| Autor: | Xia Sun, Brian Oliver, Marie-Laure Samson, Leonard Rabinow, David Sturgill, Harold E. Smith, John H. Malone |
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| Přispěvatelé: | Neuroendocrinologie moléculaire de la prise alimentaire, Centre de Neurosciences Paris-Sud (CNPS), Université Paris-Sud - Paris 11 (UP11)-Centre National de la Recherche Scientifique (CNRS)-Université Paris-Sud - Paris 11 (UP11)-Centre National de la Recherche Scientifique (CNRS), Développement et évolution (DE), Université Paris-Sud - Paris 11 (UP11)-Centre National de la Recherche Scientifique (CNRS)-Université Paris-Sud - Paris 11 (UP11)-Centre National de la Recherche Scientifique (CNRS)-Centre de Neurosciences Paris-Sud (CNPS), Université Paris-Sud - Paris 11 (UP11)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Université Paris-Sud - Paris 11 (UP11)-Centre National de la Recherche Scientifique (CNRS)-Université Paris-Sud - Paris 11 (UP11)-Centre National de la Recherche Scientifique (CNRS)-Immunite anti-tumorale et chimiotactisme. Adenocarcinomes et métastases, Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR50-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Université Côte d'Azur (UCA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR50-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Université Côte d'Azur (UCA)-Centre de Neurosciences Paris-Sud (CNPS) |
| Jazyk: | angličtina |
| Rok vydání: | 2013 |
| Předmět: |
Male
Molecular Sequence Data RNA-Seq Computational biology Biochemistry 03 medical and health sciences 0302 clinical medicine Structural Biology Animals Protein Isoforms Computer Simulation splice RNA Messenger Molecular Biology Gene ComputingMilieux_MISCELLANEOUS 030304 developmental biology Genetics 0303 health sciences Base Sequence Models Genetic biology Sequence Analysis RNA Methodology Article Gene Expression Profiling Applied Mathematics Alternative splicing Computational Biology biology.organism_classification Computer Science Applications Gene expression profiling Alternative Splicing RNA splicing Drosophila Female [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC] Drosophila melanogaster DNA microarray Software 030217 neurology & neurosurgery |
| Zdroj: | BMC Bioinformatics BMC Bioinformatics, BioMed Central, 2013, pp.320. ⟨10.1186/1471-2105-14-320⟩ |
| ISSN: | 1471-2105 |
| DOI: | 10.1186/1471-2105-14-320⟩ |
| Popis: | The production of multiple transcript isoforms from one gene is a major source of transcriptome complexity. RNA-Seq experiments, in which transcripts are converted to cDNA and sequenced, allow the resolution and quantification of alternative transcript isoforms. However, methods to analyze splicing are underdeveloped and errors resulting in incorrect splicing calls occur in every experiment. We used RNA-Seq data to develop sequencing and aligner error models. By applying these error models to known input from simulations, we found that errors result from false alignment to minor splice motifs and antisense stands, shifted junction positions, paralog joining, and repeat induced gaps. By using a series of quantitative and qualitative filters, we eliminated diagnosed errors in the simulation, and applied this to RNA-Seq data from Drosophila melanogaster heads. We used high-confidence junction detections to specifically interrogate local splicing differences between transcripts. This method out-performed commonly used RNA-seq methods to identify known alternative splicing events in the Drosophila sex determination pathway. We describe a flexible software package to perform these tasks called Splicing Analysis Kit (Spanki), available at http://www.cbcb.umd.edu/software/spanki . Splice-junction centric analysis of RNA-Seq data provides advantages in specificity for detection of alternative splicing. Our software provides tools to better understand error profiles in RNA-Seq data and improve inference from this new technology. The splice-junction centric approach that this software enables will provide more accurate estimates of differentially regulated splicing than current tools. |
| Databáze: | OpenAIRE |
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