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Nature protocols DOI:10.1038/nprot.2013.084

De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis.

Publication TypeJournal Article
Year of Publication2013
AuthorsHaas, BJ, Papanicolaou, A, Yassour, M, Grabherr, M, Blood, PD, Bowden, J, Couger, MB, Eccles, D, Li, B, Lieber, M, Macmanes, MD, Ott, M, Orvis, J, Pochet, N, Strozzi, F, Weeks, N, Westerman, R, William, T, Dewey, CN, Henschel, R, Leduc, RD, Friedman, N, Regev, A
JournalNature protocols
Volume8
Issue8
Pages1494-512
Date Published2013/08/01
ISSN1754-2189
Abstract

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.

URLhttp://dx.doi.org/10.1038/nprot.2013.084
DOI10.1038/nprot.2013.084
Pubmed

http://www.ncbi.nlm.nih.gov/pubmed/23845962?dopt=Abstract