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De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
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2013 (English)In: Nature Protocols, ISSN 1754-2189, Vol. 8, no 8, 1494-1512 p.Article in journal (Refereed) Published
Abstract [en]

De novo assembly of RNA-seq data enables researchers to study transcriptomes without the need for a genome sequence; this approach can be usefully applied, for instance, in research on 'non-model organisms' of ecological and evolutionary importance, cancer samples or the microbiome. In this protocol we describe the use of the Trinity platform for de novo transcriptome assembly from RNA-seq data in non-model organisms. We also present Trinity-supported companion utilities for downstream applications, including RSEM for transcript abundance estimation, R/Bioconductor packages for identifying differentially expressed transcripts across samples and approaches to identify protein-coding genes. In the procedure, we provide a workflow for genome-independent transcriptome analysis leveraging the Trinity platform. The software, documentation and demonstrations are freely available from http://trinityrnaseq.sourceforge.net. The run time of this protocol is highly dependent on the size and complexity of data to be analyzed. The example data set analyzed in the procedure detailed herein can be processed in less than 5 h.

Place, publisher, year, edition, pages
2013. Vol. 8, no 8, 1494-1512 p.
National Category
Natural Sciences
URN: urn:nbn:se:uu:diva-207030DOI: 10.1038/nprot.2013.084ISI: 000322228600003OAI: oai:DiVA.org:uu-207030DiVA: diva2:647010
Available from: 2013-09-10 Created: 2013-09-09 Last updated: 2013-09-10Bibliographically approved

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Grabherr, Manfred
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Department of Medical Biochemistry and MicrobiologyScience for Life Laboratory, SciLifeLab
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