AugmentingAssembly
收藏DataCite Commons2020-09-04 更新2024-07-25 收录
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https://figshare.com/articles/dataset/AugmentingAssembly/2008908
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资源简介:
Researchers interested in studying and constructing transcriptomes, especially for non-model species, face the conundrum of choosing from a number of available <i>de novo</i> 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 <i>de novo</i> 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.
提供机构:
figshare
创建时间:
2015-12-14



