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Augmenting transcriptome assembly by combiningde novoand genome-guided tools
Author(s) -
Prachi Jain,
Neeraja M. Krishnan,
Binay Panda
Publication year - 2013
Publication title -
peerj
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.927
H-Index - 70
ISSN - 2167-8359
DOI - 10.7717/peerj.133
Subject(s) - sequence assembly , computational biology , genome , de novo transcriptome assembly , biology , transcriptome , computer science , genetics , gene , gene expression
Researchers interested in studying and constructing transcriptomes, especially for non-model species, face the conundrum of choosing from a number of available de novo and genome-guided assemblers. None of the popular assembly tools in use today achieve requisite sensitivity, specificity or recovery of full-length transcripts on their own. Here, we present a comprehensive comparative study of the performance of various assemblers. Additionally, we present an approach to combinatorially augment transciptome assembly by using both de novo and genome-guided tools. In our study, we obtained the best recovery and most full-length transcripts with Trinity and TopHat1-Cufflinks, respectively. The sensitivity of the assembly and isoform recovery was superior, without compromising much on the specificity, when transcripts from Trinity were augmented with those from TopHat1-Cufflinks.

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