ChIP-seq Analysis in R (CSAR): An R package for the statistical detection of protein-bound genomic regions.
ChIP-seq Analysis in R (CSAR): An R package for the statistical detection of protein-bound genomic regions.
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DOI：
10.1186/1746-4811-7-11
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发表时间：
2011-05-09
期刊：
影响因子：
5.1
通讯作者：
Krajewski P
中科院分区：
文献类型：
--
作者：
Muiño JM;Kaufmann K;van Ham RC;Angenent GC;Krajewski P
蛋白结合基因组区域的体内检测可以通过将染色质免疫沉淀与下一代测序技术（ChIP-seq）相结合来实现。这种方法产生的大量序列数据需要以统计学上正确和计算上有效的方式进行分析。作为ChIP-seq中PCR步骤的伪影，高拷贝数DNA片段的产生是该方法偏倚的重要来源。我们在这里介绍了一个用于ChIP-seq实验统计分析的R软件包。考虑到进行测序的DNA片段的平均大小，软件计算单核苷酸读段富集值。标准化后，使用基于比率检验或泊松分布的检验比较样品和对照。通过随机排列得到控制错误发现率的测试统计量阈值。通过在C++中实现最耗时的函数并将其集成到R包中来实现计算效率。模拟和实验ChIP-seq数据的分析，以证明我们的方法对PCR伪影的鲁棒性和其适当的控制错误率。软件ChIP-seq Analysis in R（CSAR）可通过分析ChIP-seq实验快速准确地检测蛋白质结合的基因组区域。与现有的方法相比，我们发现，我们的包显示出更大的鲁棒性对PCR伪影和更好的控制错误率。
In vivo detection of protein-bound genomic regions can be achieved by combining chromatin-immunoprecipitation with next-generation sequencing technology (ChIP-seq). The large amount of sequence data produced by this method needs to be analyzed in a statistically proper and computationally efficient manner. The generation of high copy numbers of DNA fragments as an artifact of the PCR step in ChIP-seq is an important source of bias of this methodology. We present here an R package for the statistical analysis of ChIP-seq experiments. Taking the average size of DNA fragments subjected to sequencing into account, the software calculates single-nucleotide read-enrichment values. After normalization, sample and control are compared using a test based on the ratio test or the Poisson distribution. Test statistic thresholds to control the false discovery rate are obtained through random permutations. Computational efficiency is achieved by implementing the most time-consuming functions in C++ and integrating these in the R package. An analysis of simulated and experimental ChIP-seq data is presented to demonstrate the robustness of our method against PCR-artefacts and its adequate control of the error rate. The software ChIP-seq Analysis in R (CSAR) enables fast and accurate detection of protein-bound genomic regions through the analysis of ChIP-seq experiments. Compared to existing methods, we found that our package shows greater robustness against PCR-artefacts and better control of the error rate.
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影响因子：
64.5
作者：
Peng JC;Valouev A;Swigut T;Zhang J;Zhao Y;Sidow A;Wysocka J
通讯作者：
Wysocka J
影响因子：
12.3
作者：
Robinson MD;Oshlack A
通讯作者：
Oshlack A
影响因子：
46.9
作者：
Ji, Hongkai;Jiang, Hui;Ma, Wenxiu;Johnson, David S.;Myers, Richard M.;Wong, Wing H.
通讯作者：
Wong, Wing H.
DOI：
10.1093/bioinformatics/btp472
发表时间：
2009-10-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Nicol JW;Helt GA;Blanchard SG Jr;Raja A;Loraine AE
通讯作者：
Loraine AE
影响因子：
48
作者：
Pepke, Shirley;Wold, Barbara;Mortazavi, Ali
通讯作者：
Mortazavi, Ali