KMS Of Academy of mathematics and systems sciences, CAS
| MSIQ: JOINT MODELING OF MULTIPLE RNA-SEQ SAMPLES FOR ACCURATE ISOFORM QUANTIFICATION | |
Li, Wei Vivian1; Zhao, Anqi2; Zhang, Shihua3 ; Li, Jingyi Jessica1
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| 2018-03-01 | |
| Source Publication | ANNALS OF APPLIED STATISTICS
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| ISSN | 1932-6157 |
| Volume | 12Issue:1Pages:510-539 |
| Abstract | Next-generation RNA sequencing (RNA-seq) technology has been widely used to assess full-length RNA isoform abundance in a high-throughput manner. RNA-seq data offer insight into gene expression levels and transcriptome structures, enabling us to better understand the regulation of gene expression and fundamental biological processes. Accurate isoform quantification from RNA-seq data is challenging due to the information loss in sequencing experiments. A recent accumulation of multiple RNA-seq data sets from the same tissue or cell type provides new opportunities to improve the accuracy of isoform quantification. However, existing statistical or computational methods for multiple RNA-seq samples either pool the samples into one sample or assign equal weights to the samples when estimating isoform abundance. These methods ignore the possible heterogeneity in the quality of different samples and could result in biased and unrobust estimates. In this article, we develop a method, which we call "joint modeling of multiple RNA-seq samples for accurate isoform quantification" (MSIQ), for more robust isoform quantification by integrating multiple RNA-seq samples under a Bayesian framework. Our method aims to (1) identify a consistent group of samples with homogeneous quality and (2) improve isoform quantification accuracy by jointly modeling multiple RNA-seq samples and allowing for higher weights on the consistent group. We show that MSIQ provides a consistent estimator of isoform abundance, and we demonstrate the accuracy and effectiveness of MSIQ compared with alternative methods through simulation studies on D. melanogaster genes. We justify MSIQ's advantages over existing approaches via application studies on real RNA-seq data of human embryonic stem cells, brain tissues, and the HepG2 immortalized cell line. We also perform a comprehensive analysis of how the isoform quantification accuracy would be affected by RNA-seq sample heterogeneity and different experimental protocols. |
| Keyword | Isoform abundance estimation joint inference from multiple samples RNA sequencing Bayesian hierarchical models Gibbs sampling data heterogeneity |
| DOI | 10.1214/17-AOAS1100 |
| Language | 英语 |
| Funding Project | National Natural Science Foundation of China[61379092] ; National Natural Science Foundation of China[61422309] ; National Natural Science Foundation of China[61621003] ; National Natural Science Foundation of China[11661141019] ; Strategic Priority Research Program of the Chinese Academy of Sciences (CAS)[XDB13040600] ; CAS Frontier Science Research Key Project for Top Young Scientist[QYZDB-SSW-SYS008] ; UCLA Department of Statistics ; Hellman Fellowship ; PhRMA Foundation Research Starter Grant in Informatics ; National Science Foundation[DMS-1613338] ; National Institutes of Health / National Institute of General Medical Sciences[R01GM120507] |
| WOS Research Area | Mathematics |
| WOS Subject | Statistics & Probability |
| WOS ID | WOS:000429908100020 |
| Publisher | INST MATHEMATICAL STATISTICS |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.amss.ac.cn/handle/2S8OKBNM/29958 |
| Collection | 应用数学研究所 |
| Corresponding Author | Li, Wei Vivian |
| Affiliation | 1.Univ Calif Los Angeles, Dept Stat, 8125 Math Sci Bldg, Los Angeles, CA 90095 USA 2.Harvard Univ, Dept Stat, Sci Ctr 7th Floor,One Oxford St, Cambridge, MA 02138 USA 3.Chinese Acad Sci, Acad Math & Syst Sci, NCMIS, CEMS,RCSDS, 55 Zhongguancun East Rd, Beijing 100190, Peoples R China |
| Recommended Citation GB/T 7714 | Li, Wei Vivian,Zhao, Anqi,Zhang, Shihua,et al. MSIQ: JOINT MODELING OF MULTIPLE RNA-SEQ SAMPLES FOR ACCURATE ISOFORM QUANTIFICATION[J]. ANNALS OF APPLIED STATISTICS,2018,12(1):510-539. |
| APA | Li, Wei Vivian,Zhao, Anqi,Zhang, Shihua,&Li, Jingyi Jessica.(2018).MSIQ: JOINT MODELING OF MULTIPLE RNA-SEQ SAMPLES FOR ACCURATE ISOFORM QUANTIFICATION.ANNALS OF APPLIED STATISTICS,12(1),510-539. |
| MLA | Li, Wei Vivian,et al."MSIQ: JOINT MODELING OF MULTIPLE RNA-SEQ SAMPLES FOR ACCURATE ISOFORM QUANTIFICATION".ANNALS OF APPLIED STATISTICS 12.1(2018):510-539. |
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