  RNA-seq allows detection and precise quantification of transcripts, provides
comprehensive understanding of exon/intron boundaries, aids discovery of
alternatively spliced isoforms and fusion transcripts along with measurement of
allele-specific expression. Researchers interested in studying and constructing
transcriptomes, especially for non-model species, often face the conundrum of
choosing from a number of available de novo and genome-guided assemblers. A
comprehensive comparative study is required to assess and evaluate their
efficiency and sensitivity for transcript assembly, reconstruction and
recovery. None of the popular assembly tools in use today achieves requisite
sensitivity, specificity or recovery of full-length transcripts on its own.
Hence, it is imperative that methods be developed in order to augment
assemblies generated from multiple tools, with minimal compounding of error.
Here, we present an approach to combinatorially augment transciptome assembly
based on a rigorous comparative study of popular de novo and genome-guided
transcriptome assembly tools.
