QuaPra: Efficient transcript assembly and quantification using quadratic programming with Apriori algorithm

被引：0

作者：

Xiangjun Ji ^{[1
]}

Weida Tong ^{[2
]}

Baitang Ning ^{[2
]}

Christopher E.Mason ^{[3
,4
,5
]}

David P.Kreil ^{[6
]}

Pawel P.Labaj ^{[6
,7
,8
]}

Geng Chen ^{[1
]}

Tieliu Shi ^{[1
,9
]}

机构：

[1] The Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University

[2] National Center for Toxicological Research, U.S.Food and Drug Administration

[3] Department of Physiology and Biophysics, Weill Cornell Medicine

[4] Malopolska Centre of Biotechnology, Jagiellonian University

[5] APART Fellow, Austrian Academy of Science

[6] National Center for International Research of Biological Targeting Diagnosis and Therapy, Guangxi Key Laboratory of Biological Targeting Diagnosis and Therapy Research, Collaborative Innovation Center for Targeting Tumor Diagnosis and Therapy, Guangxi Medi

来源：

Science China(Life Sciences) | 2019年 / 07期

基金：

国家高技术研究发展计划(863计划); 美国国家科学基金会;

关键词：

RNA-Seq; transcriptome reconstruction; transcript assembly; transcript quantification;

D O I：

暂无

中图分类号：

Q811.4 [生物信息论];

学科分类号：

0711 ; 0831 ;

摘要：

RNA sequencing(RNA-seq) has greatly facilitated the exploring of transcriptome landscape for diverse organisms. However,transcriptome reconstruction is still challenging due to various limitations of current tools and sequencing technologies. Here, we introduce an efficient tool, QuaPra(Quadratic Programming combined with Apriori), for accurate transcriptome assembly and quantification. QuaPra could detect at least 26.5% more low abundance(0.1–1 FPKM) transcripts with over 2.7% increase of sensitivity and precision on simulated data compared to other currently popular tools. Moreover, around one-quarter more known transcripts were correctly assembled by QuaPra than other assemblers on real sequencing data. QuaPra is freely available at http://www.megabionet.org/QuaPra/.

引用

页码：937 / 946

页数：10

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