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

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    De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis.Crossref
    This article is really useful and beneficial to Researcher with De novo assembly.
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        Rated 5 of 5.
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        Rated 5 of 5.
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        Rated 5 of 5.
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        Rated 5 of 5.
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        Rated 5 of 5.
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    De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis.

    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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      Review information

      10.14293/S2199-1006.1.SOR-CHEM.AEHHWR.v1.RJOVMN

      This work has been published open access under Creative Commons Attribution License CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com.

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      Respected,

      This Protocol publication is useful to Scientist with minimal and expert Bioinformatics knowledge. All the methodology steps are clearly described with appropriate commands and have shown output results in pictorial format. This Trinity platform will be greatly helpful to Researcher to imply this tool into their own analysis.

      Sincerely!

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