De novo transcriptome assembly of RNA-Seq reads with different strategies

查看全文 作　　者：CHEN [1]Geng;YIN [1]KangPing;WANG [2]Charles;SHI [1]TieLiu

机构地区：[1]Center for Bioinformatics and Computational Biology, Institute of Biomedical Sciences, School of Life Science, East China Normal University, Shanghai 200241, China;[2]Functional Genomics Core, Beckman Research Institute, City of Hope Comprehensive Cancer Center, Duarte, CA 91010, USA

出　　处：《Science China(Life Sciences)》索引2011年第54卷第12期,共5页

基　　金：supported by the National Basic Research Program of China (Grant Nos. 2010CB945401, 2007CB108800);National Natural Science Foundation of China (Grant Nos. 30870575, 31071162,31000590);the Science and Technology Commission of Shanghai Municipality (Grant No. 11DZ2260300) 摘　　要：De novo transcriptome assembly is an important approach in RNA-Seq data analysis and it can help us to reconstruct the transcriptome and investigate gene expression profiles without reference genome sequences.We carried out transcriptome assemblies with two RNA-Seq datasets generated from human brain and cell line,respectively.We then determined an efficient way to yield an optimal overall assembly using three different strategies.We first assembled brain and cell line transcriptome using a single k-mer length.Next we tested a range of values of k-mer length and coverage cutoff in assembling.Lastly,we combined the assembled contigs from a range of k values to generate a final assembly.By comparing these assembly results,we found that using only one k-mer value for assembly is not enough to generate good assembly results,but combining the contigs from different k-mer values could yield longer contigs and greatly improve the overall assembly. 关键词：整体组装 RNA序列转录组读取基因表达谱基因组序列重叠群装配结

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De novo transcriptome assembly of RNA-Seq reads with different strategies

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