Evaluation of de novo transcriptome assemblies from RNA-Seq data
Bo Li, Nathanael Fillmore, Yongsheng Bai, Mike Collins, James A Thomson, Ron Stewart, Colin 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. Our experiments 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. With the guidance of RSEM-EVAL, we assembled the transcriptome of the regenerating axolotl limb; this assembly compares favorably to a previous assembly.
02 /Specification & Classification
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