De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis. Haas, B., Papanicolaou, A., Yassour, M., Grabherr, M., Blood, P., Bowden, J., Couger, M., Eccles, D., Li, B., Lieber, M., MacManes, M., Ott, M., Orvis, J., Pochet, N., Strozzi, F., Weeks, N., Westerman, R., William, T., Dewey, C., Henschel, R., e., a., Haas, B., J., Papanicolaou, A., Yassour, M., Grabherr, M., Blood, P., D., Bowden, J., Couger, M., B., Eccles, D., Li, B., Lieber, M., Macmanes, M., D., Ott, M., Orvis, J., Pochet, N., Strozzi, F., Weeks, N., Westerman, R., William, T., Dewey, C., N., Henschel, R., Leduc, R., D., Friedman, N., Regev, A., & others Nature Protocols, 8(8):1494-1512, 2013.
De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis [link]Website  abstract   bibtex   
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.
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 title = {De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis},
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 year = {2013},
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 keywords = {Base Sequence,Gene Expression Profiling,RNA,Sc,Software,Transcriptome,accuracy,article,clinical protocol,data analys,transcriptome},
 pages = {1494-1512},
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 notes = {<b>From Duplicate 1 (<i>De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis</i> - Haas, B J; Papanicolaou, A; Yassour, M; Grabherr, M; Blood, P D; Bowden, J; Couger, M B; Eccles, D; Li, B; Lieber, M; MacManes, M D; Ott, M; Orvis, J; Pochet, N; Strozzi, F; Weeks, N; Westerman, R; William, T; Dewey, C N; Henschel, R; Leduc, R D; Friedman, N; Regev, A; others)<br/></b><br/><b>From Duplicate 2 (<i>De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis</i> - Haas, B J; Papanicolaou, A; Yassour, M; Grabherr, M; Blood, P D; Bowden, J; Couger, M B; Eccles, D; Li, B; Lieber, M; Macmanes, M D; Ott, M; Orvis, J; Pochet, N; Strozzi, F; Weeks, N; Westerman, R; William, T; Dewey, C N; Henschel, R; Leduc, R D; Friedman, N; Regev, A)<br/></b><br/>cited By 1139<br/><br/><b>From Duplicate 2 (<i>De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis</i> - Haas, B., Papanicolaou, A., Yassour, M., Grabherr, M., Blood, P., Bowden, J., Couger, M., Eccles, D., Li, B., Lieber, M., MacManes, M., Ott, M., Orvis, J., Pochet, N., Strozzi, F., Weeks, N., Westerman, R., William, T., Dewey, C., Henschel, R., et al; Haas, B J; Papanicolaou, A; Yassour, M; Grabherr, M; Blood, P D; Bowden, J; Couger, M B; Eccles, D; Li, B; Lieber, M; Macmanes, M D; Ott, M; Orvis, J; Pochet, N; Strozzi, F; Weeks, N; Westerman, R; William, T; Dewey, C N; Henschel, R; Leduc, R D; Friedman, N; Regev, A; others)<br/></b><br/><b>From Duplicate 2 (<i>De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis</i> - Haas, B J; Papanicolaou, A; Yassour, M; Grabherr, M; Blood, P D; Bowden, J; Couger, M B; Eccles, D; Li, B; Lieber, M; Macmanes, M D; Ott, M; Orvis, J; Pochet, N; Strozzi, F; Weeks, N; Westerman, R; William, T; Dewey, C N; Henschel, R; Leduc, R D; Friedman, N; Regev, A)<br/></b><br/>cited By 1139<br/><br/><b>From Duplicate 3 (<i>De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis</i> - Haas, B J; Papanicolaou, A; Yassour, M; Grabherr, M; Blood, P D; Bowden, J; Couger, M B; Eccles, D; Li, B; Lieber, M; MacManes, M D; Ott, M; Orvis, J; Pochet, N; Strozzi, F; Weeks, N; Westerman, R; William, T; Dewey, C N; Henschel, R; Leduc, R D; Friedman, N; Regev, A; others)<br/></b><br/><b>From Duplicate 2 (<i>De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis</i> - Haas, B J; Papanicolaou, A; Yassour, M; Grabherr, M; Blood, P D; Bowden, J; Couger, M B; Eccles, D; Li, B; Lieber, M; Macmanes, M D; Ott, M; Orvis, J; Pochet, N; Strozzi, F; Weeks, N; Westerman, R; William, T; Dewey, C N; Henschel, R; Leduc, R D; Friedman, N; Regev, A)<br/></b><br/>cited By 1139},
 private_publication = {false},
 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.},
 bibtype = {article},
 author = {Haas, B., Papanicolaou, A., Yassour, M., Grabherr, M., Blood, P., Bowden, J., Couger, M., Eccles, D., Li, B., Lieber, M., MacManes, M., Ott, M., Orvis, J., Pochet, N., Strozzi, F., Weeks, N., Westerman, R., William, T., Dewey, C., Henschel, R., et al and Haas, B J and Papanicolaou, A and Yassour, M and Grabherr, M and Blood, P D and Bowden, J and Couger, M B and Eccles, D and Li, B and Lieber, M and Macmanes, M D and Ott, M and Orvis, J and Pochet, N and Strozzi, F and Weeks, N and Westerman, R and William, T and Dewey, C N and Henschel, R and Leduc, R D and Friedman, N and Regev, A and others, undefined},
 journal = {Nature Protocols},
 number = {8}
}

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