Transcript and gene quantification is the first stepin many RNA-seq analyses. While many factors and propertiesof experimental RNA-seq data likely contribute to differences inaccuracy between various approaches to quantification, it has been demonstrated that quantification accuracy generally benefits from considering, during alignment, potential genomic origins for se-quenced fragments that reside outside of the annotated transcriptome. Recently, Varabyou et al. demonstrated that the presenceof transcriptional noise leads to systematic errors in the ability oftools, particularly annotation-based ones, to accurately estimate transcript expression. Here, we confirm the findings of Varabyouet al. using the simulation framework they have provided. Using the same data, we also examine the methodology of Srivastava et al. as implemented in recent versions of salmon, and show thatit substantially enhances the accuracy of annotation-based transcript quantification in these data.

中文翻译：

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考虑到意外来源的片段，可改善专注于增加真实性的RNA-seq模拟中的转录本定量

转录本和基因定量是许多RNA序列分析的第一步。尽管实验RNA序列数据的许多因素和特性可能会导致各种量化方法之间的准确性差异，但事实证明，在比对过程中，考虑到位于注释外的序列片段的潜在基因组来源，通常可以从中获得量化准确性转录组。最近，Varabyou等人。证明转录噪声的存在会导致工具（尤其是基于注释的工具）准确估计转录本表达能力的系统性错误。在这里，我们确认Varabyouet等人的发现。使用他们提供的仿真框架。使用相同的数据，我们还研究了Srivastava等人的方法。