Unique Molecular Identifiers Don't Need to be Unique: A Collision-Aware Estimator for RNA-Seq Quantification.

IF 1.3 4区 生物学 Q4 BIOCHEMICAL RESEARCH METHODS
Dylan Agyemang, Rafael A Irizarry, Tavor Z Baharav
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引用次数: 0

Abstract

RNA-sequencing (RNA-seq) relies on Unique Molecular Identifiers (UMIs) to accurately quantify gene expression after PCR amplification. Longer UMIs minimize collisions, where two distinct transcripts are assigned the same UMI, at the expense of increased sequencing and synthesis costs. However, it is not clear how long UMIs need to be in practice, especially given the nonuniformity of the empirical UMI distribution. In this work, we develop a method-of-moments estimator that accounts for UMI collisions, accurately quantifying gene expression and preserving downstream biological insights. We show that UMIs need not be unique: shorter UMIs can be used with a more sophisticated estimator.

唯一分子标识符不需要是唯一的:用于RNA-Seq定量的冲突感知估计器。
rna测序(RNA-seq)依靠独特分子标识符(Unique Molecular Identifiers, UMIs)准确定量PCR扩增后的基因表达。较长的UMI最小化了冲突,其中两个不同的转录本被分配相同的UMI,以增加测序和合成成本为代价。然而,目前尚不清楚UMIs在实践中需要多长时间,特别是考虑到经验UMI分布的不均匀性。在这项工作中,我们开发了一种矩量估计方法,该方法可以解释UMI碰撞,准确量化基因表达并保留下游生物学见解。我们表明umi不需要是唯一的:更短的umi可以与更复杂的估计器一起使用。
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来源期刊
Journal of Computational Biology
Journal of Computational Biology 生物-计算机:跨学科应用
CiteScore
3.60
自引率
5.90%
发文量
113
审稿时长
6-12 weeks
期刊介绍: Journal of Computational Biology is the leading peer-reviewed journal in computational biology and bioinformatics, publishing in-depth statistical, mathematical, and computational analysis of methods, as well as their practical impact. Available only online, this is an essential journal for scientists and students who want to keep abreast of developments in bioinformatics. Journal of Computational Biology coverage includes: -Genomics -Mathematical modeling and simulation -Distributed and parallel biological computing -Designing biological databases -Pattern matching and pattern detection -Linking disparate databases and data -New tools for computational biology -Relational and object-oriented database technology for bioinformatics -Biological expert system design and use -Reasoning by analogy, hypothesis formation, and testing by machine -Management of biological databases
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