Evaluation of de novo transcriptome assemblies from RNA-Seq data View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2014-12

AUTHORS

Bo Li, Nathanael Fillmore, Yongsheng Bai, Mike Collins, James A Thomson, Ron Stewart, Colin N Dewey

ABSTRACT

De novo RNA-Seq assembly facilitates the study of transcriptomes for species without sequenced genomes, but it is challenging to select the most accurate assembly in this context. To address this challenge, we developed a model-based score, RSEM-EVAL, for evaluating assemblies when the ground truth is unknown. We show that RSEM-EVAL correctly reflects assembly accuracy, as measured by REF-EVAL, a refined set of ground-truth-based scores that we also developed. Guided by RSEM-EVAL, we assembled the transcriptome of the regenerating axolotl limb; this assembly compares favorably to a previous assembly. A software package implementing our methods, DETONATE, is freely available at http://deweylab.biostat.wisc.edu/detonate. More... »

PAGES

553

References to SciGraph publications

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/s13059-014-0553-5

    DOI

    http://dx.doi.org/10.1186/s13059-014-0553-5

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1027805047

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/25608678


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