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Improvements in short-read sequencing technology combined with rapidly decreasing prices have enabled the use of RNA-seq to assay the transcriptome of species whose genome has not been sequenced. {\it De-novo} transcriptome assembly attempts to reconstruct the original transcript sequences from short reads. Transcriptome assemblies are relied upon for RNA-Seq gene expression studies, phylogenetic analyses, and molecular tooling. It is therefore important to ensure that assemblies are as accurate as possible, but to date there are no tools for deep quality assessment of assemblies. We present \textbf{Transrate}, an open source command-line program that analyses assembly quality based on contig metrics, read mapping, comparison to reference species, and network analysis. We demonstrate using both published and simulated data that using transrate identified the strengths and weaknesses of different assembly strategies.