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A consensus-based ensemble approach to improve transcriptome assembly.

Adam VoshallSairam BeheraXiangjun LiXiao-Hong YuKushagra KapilJitender S DeogunJohn ShanklinEdgar B CahoonEtsuko N Moriyama
Published in: BMC bioinformatics (2021)
Without using a reference genome, ConSemble using four de novo assemblers achieved an accuracy up to twice as high as any de novo assemblers we compared. When a reference genome is available, ConSemble using four genome-guided assemblies removed many incorrectly assembled contigs with minimal impact on correctly assembled contigs, achieving higher precision and accuracy than individual genome-guided methods. Furthermore, ConSemble using de novo assemblers matched or exceeded the best performing genome-guided assemblers even when the transcriptomes included isoforms. We thus demonstrated that the ConSemble consensus strategy both for de novo and genome-guided assemblers can improve transcriptome assembly. The RNAseq simulation pipeline, the benchmark transcriptome datasets, and the script to perform the ConSemble assembly are all freely available from: http://bioinfolab.unl.edu/emlab/consemble/ .
Keyphrases
  • genome wide
  • single cell
  • rna seq
  • gene expression
  • dna methylation
  • clinical practice