title: Evaluation of de novo transcriptome assemblies from RNA-Seq data.
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.
authors.forename: Bo
authors.initials: B
authors.lastname: Li
authors.forename: Nathanael
authors.initials: N
authors.lastname: Fillmore
authors.forename: Yongsheng
authors.initials: Y
authors.lastname: Bai
authors.forename: Mike
authors.initials: M
authors.lastname: Collins
authors.forename: James A
authors.initials: JA
authors.lastname: Thomson
authors.forename: Ron
authors.initials: R
authors.lastname: Stewart
authors.forename: Colin N
authors.initials: CN
authors.lastname: Dewey
mesh_terms: D000465:Algorithms; D000818:Animals; D019295:Computational Biology / Q000379:methods; D003198:Computer Simulation; D020869:Gene Expression Profiling / Q000379:methods; D017423:Sequence Analysis, RNA / Q000379:methods*; D012984:Software