RSEM-EVAL – for evaluating assemblies when the ground truth is unknown

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, a team led by researchers at the University of Wisconsin, Madison developed a model-based score, RSEM-EVAL, for evaluating assemblies when the ground truth is unknown. They show that RSEM-EVAL correctly reflects assembly accuracy, as measured by REF-EVAL, a refined set of ground-truth-based scores that the team also developed. Guided by RSEM-EVAL, the researchers assembled the transcriptome of the regenerating axolotl limb; this assembly compares favorably to a previous assembly.

rna-seq

RSEM-EVAL correctly selects the Trinity assembly of reads originating from a transcript of mouse geneRpl24 as the best among the default assemblies from Trinity, Oases and SOAPdenovo-Trans.

Availability – A software package implementing our methods, DETONATE, is freely available at http://deweylab.biostat.wisc.edu/detonate

Li B, Fillmore N, Bai Y, Collins M, Thomson JA, Stewart R, Dewey CN. (2014) Evaluation of de novo transcriptome assemblies from RNA-Seq data. Genome Biol 15(12):553. [article]

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