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Relative Abundance of Transcripts (RATs): Identifying differential isoform abundance from RNA-seq

机译:笔录的相对丰度(RAT):从RNA序列中识别差异同工型丰度

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摘要

The biological importance of changes in RNA expression is reflected by the wide variety of tools available to characterise these changes from RNA-seq data. Several tools exist for detecting differential transcript isoform usage (DTU) from aligned or assembled RNA-seq data, but few exist for DTU detection from alignment-free RNA-seq quantifications. We present the RATs, an R package that identifies DTU transcriptome-wide directly from transcript abundance estimates. RATs is unique in applying bootstrapping to estimate the reliability of detected DTU events and shows good performance at all replication levels (median false positive fraction < 0.05). We compare RATs to two existing DTU tools, DRIM-Seq & SUPPA2, using two publicly available simulated RNA-seq datasets and a published human RNA-seq dataset, in which 248 genes have been previously identified as displaying significant DTU. RATs with default threshold values on the simulated Human data has a sensitivity of 0.55, a Matthews correlation coefficient of 0.71 and a false discovery rate (FDR) of 0.04, outperforming both other tools. Applying the same thresholds for SUPPA2 results in a higher sensitivity (0.61) but poorer FDR performance (0.33). RATs and DRIM-seq use different methods for measuring DTU effect-sizes complicating the comparison of results between these tools, however, for a likelihood-ratio threshold of 30, DRIM-Seq has similar FDR performance to RATs (0.06), but worse sensitivity (0.47). These differences persist for the simulated drosophila dataset. On the published human RNA-seq dataset the greatest agreement between the tools tested is 53%, observed between RATs and SUPPA2. The bootstrapping quality filter in RATs is responsible for removing the majority of DTU events called by SUPPA2 that are not reported by RATs. All methods, including the previously published qRT-PCR of three of the 248 detected DTU events, were found to be sensitive to annotation differences between Ensembl v60 and v87.
机译:RNA表达变化的生物学重要性反映在可用于从RNA-seq数据表征这些变化的多种工具中。存在几种用于从比对或组装的RNA-seq数据中检测差异转录亚型用法(DTU)的工具,但很少有用于从无比对的RNA-seq定量检测DTU的工具。我们介绍了RAT,这是一个R包,可直接从转录本丰度估算值确定整个DTU转录组。 RAT在应用引导程序来估计检测到的DTU事件的可靠性方面具有独特性,并且在所有复制级别上均具有良好的性能(中位数假阳性分数<0.05)。我们使用两个可公开获得的模拟RNA-seq数据集和已发布的人类RNA-seq数据集将RAT与两个现有DTU工具DRIM-Seq和SUPPA2进行了比较,其中先前已确定248个基因显示了重要的DTU。在模拟的人类数据上具有默认阈值的RAT的灵敏度为0.55,Matthews相关系数为0.71,错误发现率(FDR)为0.04,优于其他两个工具。对SUPPA2应用相同的阈值会导致较高的灵敏度(0.61)但较差的FDR性能(0.33)。 RAT和DRIM-seq使用不同的方法来测量DTU效果大小,这使这些工具之间的结果比较变得复杂,但是,对于30的似然比阈值,DRIM-Seq具有与RAT相似的FDR性能(0.06),但灵敏度较差(0.47)。对于模拟的果蝇数据集,这些差异仍然存在。在已发布的人类RNA-seq数据集上,在RAT和SUPPA2之间观察到的测试工具之间的最大一致性为53%。 RAT中的引导质量过滤器负责删除RAT未报告的SUPPA2调用的大多数DTU事件。发现所有方法,包括先前发布的248个检测到的DTU事件中的三个事件的qRT-PCR,都对Ensembl v60和v87之间的注释差异敏感。

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