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

Xiangjun Ji; Weida Tong; Baitang Ning; Christopher E Mason; David P Kreil; Pawel P Labaj; Geng Chen; Tieliu Shi

doi:10.1007/s11427-018-9433-3

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

Sci China Life Sci. 2019 Jul;62(7):937-946. doi: 10.1007/s11427-018-9433-3. Epub 2019 May 22.

Authors

Xiangjun Ji¹, Weida Tong², Baitang Ning², Christopher E Mason^{3

4

5}, David P Kreil⁶, Pawel P Labaj^{6

7

8}, Geng Chen⁹, Tieliu Shi^{10

11}

Affiliations

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, Shanghai, 200241, China.
² National Center for Toxicological Research, U.S. Food and Drug Administration, 3900 NCTR RD, Jefferson, AR, 72079, USA.
³ Department of Physiology and Biophysics, Weill Cornell Medicine, New York, 10065, USA.
⁴ The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, New York, 10021, USA.
⁵ Feil Family Brain & Mind Research Institute, New York, 10065, USA.
⁶ Chair of Bioinformatics Research Group, Boku University, Vienna, A-1190, Austria.
⁷ Malopolska Centre of Biotechnology, Jagiellonian University, Krakow, 30-387, Poland.
⁸ APART Fellow, Austrian Academy of Science, Vienna, A-1190, Austria.
⁹ 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, Shanghai, 200241, China. gchen@bio.ecnu.edu.cn.
¹⁰ 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, Shanghai, 200241, China. tlshi@bio.ecnu.edu.cn.
¹¹ 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 Medical University, Nanning, 530021, China. tlshi@bio.ecnu.edu.cn.

PMID: 31124003
DOI: 10.1007/s11427-018-9433-3

Abstract

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 2.1% 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 https://doi.org/www.megabionet.org/QuaPra/ .

Keywords: RNA-Seq; transcript assembly; transcript quantification; transcriptome reconstruction.

MeSH terms

Algorithms
Computer Simulation
Gene Expression Profiling
High-Throughput Nucleotide Sequencing
Humans
Internet
Sequence Analysis, RNA / methods*
Software
Transcription, Genetic
Transcriptome / genetics