DiffSplice: the genome-wide detection of differential splicing events with RNA-seq.
DiffSplice: the genome-wide detection of differential splicing events with RNA-seq.
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DOI：
10.1093/nar/gks1026
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发表时间：
2013-01
影响因子：
14.9
通讯作者：
Liu J
中科院分区：
文献类型：
--
作者：
Hu Y;Huang Y;Du Y;Orellana CF;Singh D;Johnson AR;Monroy A;Kuan PF;Hammond SM;Makowski L;Randell SH;Chiang DY;Hayes DN;Jones C;Liu Y;Prins JF;Liu J
RNA转录组响应于细胞分化以及环境因素而变化，并且可以通过转录异构体的多样性和丰度来表征。差异转录分析，检测不同细胞的转录组之间的差异，可以提高对细胞分化和发育的理解，并能够识别分类疾病类型的生物标志物。高通量短读RNA测序技术的可用性提供了转录组的深入采样，使得准确检测转录组之间的差异成为可能。在这篇文章中，我们提出了一种新的方法来检测和可视化的差异转录。我们的方法不依赖于转录本或基因注释。它还避免了对完整转录本推断和定量的需要，这是一个具有挑战性的问题，因为短的读取长度，以及各种采样偏差。相反，我们的方法采用分而治之的方法来定位转录组之间的差异，以选择性剪接模块（ASM）的形式，转录异构体的分歧。我们的方法从剪接图中识别ASM开始，剪接图直接从RNA-seq读取比对预测的外显子和内含子构建。估计每个样品中存在于每个ASM中的可变剪接同种型的丰度，并在样品组之间进行比较。对每个ASM应用非参数统计检验，以检测具有受控错误发现率的显著差异转录。该方法的灵敏度和特异性已使用模拟数据集进行了评估，并与其他国家的最先进的方法进行了比较。使用qRT-PCR的实验验证证实了在肺分化研究和乳腺癌数据集中差异表达的一组选定的基因，证明了该方法应用于实验生物数据集的实用性。DiffSplice软件可在http://www.netlab.uky.edu/p/bioinfo/DiffSplice上获得。
The RNA transcriptome varies in response to cellular differentiation as well as environmental factors, and can be characterized by the diversity and abundance of transcript isoforms. Differential transcription analysis, the detection of differences between the transcriptomes of different cells, may improve understanding of cell differentiation and development and enable the identification of biomarkers that classify disease types. The availability of high-throughput short-read RNA sequencing technologies provides in-depth sampling of the transcriptome, making it possible to accurately detect the differences between transcriptomes. In this article, we present a new method for the detection and visualization of differential transcription. Our approach does not depend on transcript or gene annotations. It also circumvents the need for full transcript inference and quantification, which is a challenging problem because of short read lengths, as well as various sampling biases. Instead, our method takes a divide-and-conquer approach to localize the difference between transcriptomes in the form of alternative splicing modules (ASMs), where transcript isoforms diverge. Our approach starts with the identification of ASMs from the splice graph, constructed directly from the exons and introns predicted from RNA-seq read alignments. The abundance of alternative splicing isoforms residing in each ASM is estimated for each sample and is compared across sample groups. A non-parametric statistical test is applied to each ASM to detect significant differential transcription with a controlled false discovery rate. The sensitivity and specificity of the method have been assessed using simulated data sets and compared with other state-of-the-art approaches. Experimental validation using qRT-PCR confirmed a selected set of genes that are differentially expressed in a lung differentiation study and a breast cancer data set, demonstrating the utility of the approach applied on experimental biological data sets. The software of DiffSplice is available at http://www.netlab.uky.edu/p/bioinfo/DiffSplice.
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影响因子：
46.9
作者：
Trapnell C;Williams BA;Pertea G;Mortazavi A;Kwan G;van Baren MJ;Salzberg SL;Wold BJ;Pachter L
通讯作者：
Pachter L
影响因子：
48
作者：
Katz, Yarden;Wang, Eric T.;Airoldi, Edoardo M.;Burge, Christopher B.
通讯作者：
Burge, Christopher B.
影响因子：
5.3
作者：
Muraoka-Cook, Rebecca S.;Sandahl, Melissa A.;Earp, H. Shelton, III
通讯作者：
Earp, H. Shelton, III
影响因子：
7
作者：
Li, Ruiqiang;Zhu, Hongmei;Wang, Jun
通讯作者：
Wang, Jun
DOI：
10.1145/295656.295663
发表时间：
1998-11-01
影响因子：
1.3
作者：
Buchsbaum, AL;Kaplan, H;Westbrook, JR
通讯作者：
Westbrook, JR