In the past years, de Bruijn graph methods had showed its
advantage for full-length assemblies, but chimeric k-mer nodes
limited the capability of modern de Bruijn graph algorithms
to generate accurate low-coverage assemblies. Moreover,
using shorter k-mer in de Bruijn graph assembler algorithms
produces more mis-assemblies (Schulz et al., 2012), whereas
EBARDenovo can maintain high accuracy of assembly even with a short key length (Supplementary Fig. S5). In conclusion,
the EBARDenovo algorithm is a promising new approach to
identify transcripts from RNA-Seq analysis.