title: Accuracy of RNA-Seq and its dependence on sequencing depth.
abstract: BACKGROUND
  The cost of DNA sequencing has undergone a dramatical reduction in the past decade. As a result, sequencing technologies have been increasingly applied to genomic research. RNA-Seq is becoming a common technique for surveying gene expression based on DNA sequencing. As it is not clear how increased sequencing capacity has affected measurement accuracy of mRNA, we sought to investigate that relationship.
  
  
  RESULTS
  We empirically evaluate the accuracy of repeated gene expression measurements using RNA-Seq. We identify library preparation steps prior to DNA sequencing as the main source of error in this process. Studying three datasets, we show that the accuracy indeed improves with the sequencing depth. However, the rate of improvement as a function of sequence reads is generally slower than predicted by the binomial distribution. We therefore used the beta-binomial distribution to model the overdispersion. The overdispersion parameters we introduced depend explicitly on the number of reads so that the resulting statistical uncertainty is consistent with the empirical data that measurement accuracy increases with the sequencing depth. The overdispersion parameters were determined by maximizing the likelihood. We shown that our modified beta-binomial model had lower false discovery rate than the binomial or the pure beta-binomial models.
  
  
  CONCLUSIONS
  We proposed a novel form of overdispersion guaranteeing that the accuracy improves with sequencing depth. We demonstrated that the new form provides a better fit to the data.
authors: Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030, USA.
authors: Guoshuai
authors: G
authors: Cai
authors: Hua
authors: H
authors: Li
authors: Yue
authors: Y
authors: Lu
authors: Xuelin
authors: X
authors: Huang
authors: Juhee
authors: J
authors: Lee
authors: Peter
authors: P
authors: Müller
authors: Yuan
authors: Y
authors: Ji
authors: Shoudan
authors: S
authors: Liang
mesh_terms: D020869:Gene Expression Profiling / Q000379:methods; D015723:Gene Library; D016678:Genome; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods* / Q000706:statistics & numerical data*; D015233:Models, Statistical; D012333:RNA, Messenger / Q000235:genetics*; D017422:Sequence Analysis, DNA / Q000379:methods* / Q000706:statistics & numerical data*; D017423:Sequence Analysis, RNA / Q000379:methods* / Q000706:statistics & numerical data*
chemical_list: D012333:RNA, Messenger