Flexible expressed region analysis for RNA-seq with derfinder.
Flexible expressed region analysis for RNA-seq with derfinder.
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DOI：
10.1093/nar/gkw852
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发表时间：
2017-01-25
影响因子：
14.9
通讯作者：
Jaffe AE
中科院分区：
文献类型：
--
作者：
Collado-Torres L;Nellore A;Frazee AC;Wilks C;Love MI;Langmead B;Irizarry RA;Leek JT;Jaffe AE
RNA测序（RNA-seq）数据的差异表达分析通常依赖于重建转录本或计数与已知基因结构重叠的读数。我们之前介绍了一种称为差异表达区域（DER）查找器的中间统计方法，该方法旨在识别在单碱基分辨率下显示差异表达信号的基因组连续区域，而不依赖于现有的注释或可能不准确的转录本组装。我们提出了derfinder软件，它通过以下方式改进了我们对RNA-seq分析的注释不可知方法：（i）实施一种计算效率高的bump-hunting方法来识别DER，该方法允许在大量样本中进行基因组规模的分析，（ii）引入一个灵活的统计建模框架，包括多组和时间过程分析，以及（iii）引入一组新的数据可视化用于表达区域分析。我们将这种方法应用于来自基因型组织表达（GTEx）项目和BrainSpan项目的公共RNA-seq数据，以表明derfinder允许在R中以碱基分辨率分析数百个样本，识别已知基因边界之外的表达，并可用于以碱基分辨率可视化表达区域。在模拟中，我们的基本分辨率方法可以在存在不完整注释的情况下进行发现，并且在注释完成时几乎与特征级方法一样强大。使用表达的区域水平和单个基础水平方法的Derfinder分析提供了完整转录本重建和特征水平分析之间的折衷。该包可从Bioconductor在www.bioconductor.org/packages/derfinder获得。
Differential expression analysis of RNA sequencing (RNA-seq) data typically relies on reconstructing transcripts or counting reads that overlap known gene structures. We previously introduced an intermediate statistical approach called differentially expressed region (DER) finder that seeks to identify contiguous regions of the genome showing differential expression signal at single base resolution without relying on existing annotation or potentially inaccurate transcript assembly. We present the derfinder software that improves our annotation-agnostic approach to RNA-seq analysis by: (i) implementing a computationally efficient bump-hunting approach to identify DERs that permits genome-scale analyses in a large number of samples, (ii) introducing a flexible statistical modeling framework, including multi-group and time-course analyses and (iii) introducing a new set of data visualizations for expressed region analysis. We apply this approach to public RNA-seq data from the Genotype-Tissue Expression (GTEx) project and BrainSpan project to show that derfinder permits the analysis of hundreds of samples at base resolution in R, identifies expression outside of known gene boundaries and can be used to visualize expressed regions at base-resolution. In simulations, our base resolution approaches enable discovery in the presence of incomplete annotation and is nearly as powerful as feature-level methods when the annotation is complete. derfinder analysis using expressed region-level and single base-level approaches provides a compromise between full transcript reconstruction and feature-level analysis. The package is available from Bioconductor at www.bioconductor.org/packages/derfinder.