MITIE: Simultaneous RNA-Seq-based transcript identification and quantification in multiple samples.
MITIE: Simultaneous RNA-Seq-based transcript identification and quantification in multiple samples.
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DOI：
10.1093/bioinformatics/btt442
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发表时间：
2013-10-15
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影响因子：
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通讯作者：
Rätsch G
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作者：
Behr J;Kahles A;Zhong Y;Sreedharan VT;Drewe P;Rätsch G
动机：mRNA的高通量测序（RNA- seq）在检测表达基因和重建RNA转录物方面取得了巨大的进步。然而，基因表达的广泛动态范围、技术限制和偏见，以及观察到的转录景观的复杂性，给转录组重建带来了深刻的计算挑战。结果：我们提出了新的框架MITIE（混合整数转录物鉴定），用于同时转录物重建和定量。我们定义了一个基于负二项分布的似然函数，使用正则化方法来选择一些转录本，共同解释观察到的读取数据，并展示了如何使用混合整数规划找到最优解。MITIE可以(i)利用已知的转录本，（ii）在多个样本中同时重建和量化转录本，以及（iii）解析多映射读取的位置。它是专为基因组和装配为基础的转录组重建。我们提出了一个广泛的研究基于现实的模拟RNA-Seq数据。与最先进的方法相比，MITIE被证明明显更敏感，总体上更准确。此外，当与多个样本一起使用时，MITIE产生了显著的性能提升。我们将该系统应用于38个果蝇modENCODE RNA-Seq文库，并估计了重建遗漏转录本注释的敏感性和对注释转录本的特异性。我们的研究结果证实，一个动机良好的目标与适当的优化技术相结合，可以显著改善转录组重建的现状。可用性：MITIE是用c++实现的，可以在GPL许可下从http://bioweb.me/mitie获得。联系方式：Jonas_Behr@web.de和raetsch@cbio.mskcc.org补充信息：补充数据可在Bioinformatics在线获取。
Motivation: High-throughput sequencing of mRNA (RNA-Seq) has led to tremendous improvements in the detection of expressed genes and reconstruction of RNA transcripts. However, the extensive dynamic range of gene expression, technical limitations and biases, as well as the observed complexity of the transcriptional landscape, pose profound computational challenges for transcriptome reconstruction. Results: We present the novel framework MITIE (Mixed Integer Transcript IdEntification) for simultaneous transcript reconstruction and quantification. We define a likelihood function based on the negative binomial distribution, use a regularization approach to select a few transcripts collectively explaining the observed read data and show how to find the optimal solution using Mixed Integer Programming. MITIE can (i) take advantage of known transcripts, (ii) reconstruct and quantify transcripts simultaneously in multiple samples, and (iii) resolve the location of multi-mapping reads. It is designed for genome- and assembly-based transcriptome reconstruction. We present an extensive study based on realistic simulated RNA-Seq data. When compared with state-of-the-art approaches, MITIE proves to be significantly more sensitive and overall more accurate. Moreover, MITIE yields substantial performance gains when used with multiple samples. We applied our system to 38 Drosophila melanogaster modENCODE RNA-Seq libraries and estimated the sensitivity of reconstructing omitted transcript annotations and the specificity with respect to annotated transcripts. Our results corroborate that a well-motivated objective paired with appropriate optimization techniques lead to significant improvements over the state-of-the-art in transcriptome reconstruction. Availability: MITIE is implemented in C++ and is available from http://bioweb.me/mitie under the GPL license. Contact: Jonas_Behr@web.de and raetsch@cbio.mskcc.org Supplementary information: Supplementary data are available at Bioinformatics online.