PLEK: a tool for predicting long non-coding RNAs and messenger RNAs based on an improved k-mer scheme

CORC > 昆明动物研究所 > 昆明动物研究所 > 遗传资源与进化国家重点实验室

	PLEK: a tool for predicting long non-coding RNAs and messenger RNAs based on an improved k-mer scheme
	Li AM 1,2; Zhang JY[*]1; Zhou ZY 3,4
刊名	BMC BIOINFORMATICS
	2014
卷号	15 期号:X 页码:e311
关键词	RNA-seq lncRNA k-mer Prediction de novo sequencing de novo assemble
通讯作者	jyzhang@mail.xidian.edu.cn
合作状况	其它
英文摘要	Background: High-throughput transcriptome sequencing (RNA-seq) technology promises to discover novel protein-coding and non-coding transcripts, particularly the identification of long non-coding RNAs (lncRNAs) from de novo sequencing data. This requires tools that are not restricted by prior gene annotations, genomic sequences and high-quality sequencing. Results: We present an alignment-free tool called PLEK (predictor of long non-coding RNAs and messenger RNAs based on an improved k-mer scheme), which uses a computational pipeline based on an improved k-mer scheme and a support vector machine (SVM) algorithm to distinguish lncRNAs from messenger RNAs (mRNAs), in the absence of genomic sequences or annotations. The performance of PLEK was evaluated on well-annotated mRNA and lncRNA transcripts. 10-fold cross-validation tests on human RefSeq mRNAs and GENCODE lncRNAs indicated that our tool could achieve accuracy of up to 95.6%. We demonstrated the utility of PLEK on transcripts from other vertebrates using the model built from human datasets. PLEK attained >90% accuracy on most of these datasets. PLEK also performed well using a simulated dataset and two real de novo assembled transcriptome datasets (sequenced by PacBio and 454 platforms) with relatively high indel sequencing errors. In addition, PLEK is approximately eightfold faster than a newly developed alignment-free tool, named Coding-Non-Coding Index (CNCI), and 244 times faster than the most popular alignment-based tool, Coding Potential Calculator (CPC), in a single-threading running manner. Conclusions: PLEK is an efficient alignment-free computational tool to distinguish lncRNAs from mRNAs in RNA-seq transcriptomes of species lacking reference genomes. PLEK is especially suitable for PacBio or 454 sequencing data and large-scale transcriptome data.
收录类别	SCI
资助信息	This work was supported by the Natural Science Foundation of China under Grants 61070137, 91130006, 61201312 and 61303122; and the Research Fund for the Doctoral Program of Higher Education of China (20130203110017).
语种	英语
WOS记录号	WOS:000342109200001
公开日期	2014-10-20
内容类型	期刊论文
源URL	[http://159.226.149.42:8088/handle/152453/8109]
专题	昆明动物研究所_遗传资源与进化国家重点实验室
作者单位	1.School of Computer Science and Technology, Xidian University, Xi’an, PR China 2.School of Computer Science and Engineering, Xi’an University of Technology, Xi’an, PR China 3.Department of Molecular and Cell Biology, School of Life Sciences, University of Science and Technology of China, Hefei, PR China 4.State Key Laboratory of Genetic Resources and Evolution,Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, PR China
推荐引用方式 GB/T 7714	Li AM,Zhang JY[*],Zhou ZY. PLEK: a tool for predicting long non-coding RNAs and messenger RNAs based on an improved k-mer scheme[J]. BMC BIOINFORMATICS,2014,15(X):e311.
APA	Li AM,Zhang JY[*],&Zhou ZY.(2014).PLEK: a tool for predicting long non-coding RNAs and messenger RNAs based on an improved k-mer scheme.BMC BIOINFORMATICS,15(X),e311.
MLA	Li AM,et al."PLEK: a tool for predicting long non-coding RNAs and messenger RNAs based on an improved k-mer scheme".BMC BIOINFORMATICS 15.X(2014):e311.