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Article: SOAPdenovo-Trans: De novo transcriptome assembly with short RNA-Seq reads

TitleSOAPdenovo-Trans: De novo transcriptome assembly with short RNA-Seq reads
Authors
Issue Date2014
Citation
Bioinformatics, 2014, v. 30, n. 12, p. 1660-1666 How to Cite?
AbstractMotivation: Transcriptome sequencing has long been the favored method for quickly and inexpensively obtaining a large number of gene sequences from an organism with no reference genome. Owing to the rapid increase in throughputs and decrease in costs of next- generation sequencing, RNA-Seq in particular has become the method of choice. However, the very short reads (e.g. 2 à 90 bp paired ends) from next generation sequencing makes de novo assembly to recover complete or full-length transcript sequences an algorithmic challenge. Results: Here, we present SOAPdenovo-Trans, a de novo transcriptome assembler designed specifically for RNA-Seq. We evaluated its performance on transcriptome datasets from rice and mouse. Using as our benchmarks the known transcripts from these well-annotated genomes (sequenced a decade ago), we assessed how SOAPdenovo-Trans and two other popular transcriptome assemblers handled such practical issues as alternative splicing and variable expression levels. Our conclusion is that SOAPdenovo-Trans provides higher contiguity, lower redundancy and faster execution. © 2014 The Author. Published by Oxford University Press. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/251070
ISSN
2023 Impact Factor: 4.4
2023 SCImago Journal Rankings: 2.574
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorXie, Yinlong-
dc.contributor.authorWu, Gengxiong-
dc.contributor.authorTang, Jingbo-
dc.contributor.authorLuo, Ruibang-
dc.contributor.authorPatterson, Jordan-
dc.contributor.authorLiu, Shanlin-
dc.contributor.authorHuang, Weihua-
dc.contributor.authorHe, Guangzhu-
dc.contributor.authorGu, Shengchang-
dc.contributor.authorLi, Shengkang-
dc.contributor.authorZhou, Xin-
dc.contributor.authorLam, Tak Wah-
dc.contributor.authorLi, Yingrui-
dc.contributor.authorXu, Xun-
dc.contributor.authorWong, Gane Ka Shu-
dc.contributor.authorWang, Jun-
dc.date.accessioned2018-02-01T01:54:29Z-
dc.date.available2018-02-01T01:54:29Z-
dc.date.issued2014-
dc.identifier.citationBioinformatics, 2014, v. 30, n. 12, p. 1660-1666-
dc.identifier.issn1367-4803-
dc.identifier.urihttp://hdl.handle.net/10722/251070-
dc.description.abstractMotivation: Transcriptome sequencing has long been the favored method for quickly and inexpensively obtaining a large number of gene sequences from an organism with no reference genome. Owing to the rapid increase in throughputs and decrease in costs of next- generation sequencing, RNA-Seq in particular has become the method of choice. However, the very short reads (e.g. 2 à 90 bp paired ends) from next generation sequencing makes de novo assembly to recover complete or full-length transcript sequences an algorithmic challenge. Results: Here, we present SOAPdenovo-Trans, a de novo transcriptome assembler designed specifically for RNA-Seq. We evaluated its performance on transcriptome datasets from rice and mouse. Using as our benchmarks the known transcripts from these well-annotated genomes (sequenced a decade ago), we assessed how SOAPdenovo-Trans and two other popular transcriptome assemblers handled such practical issues as alternative splicing and variable expression levels. Our conclusion is that SOAPdenovo-Trans provides higher contiguity, lower redundancy and faster execution. © 2014 The Author. Published by Oxford University Press. All rights reserved.-
dc.languageeng-
dc.relation.ispartofBioinformatics-
dc.titleSOAPdenovo-Trans: De novo transcriptome assembly with short RNA-Seq reads-
dc.typeArticle-
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.1093/bioinformatics/btu077-
dc.identifier.pmid24532719-
dc.identifier.scopuseid_2-s2.0-84902474663-
dc.identifier.hkuros239060-
dc.identifier.hkuros248456-
dc.identifier.volume30-
dc.identifier.issue12-
dc.identifier.spage1660-
dc.identifier.epage1666-
dc.identifier.eissn1460-2059-
dc.identifier.isiWOS:000338109200041-
dc.identifier.f1000718278651-

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