Next-generation sequencing (NGS) is widely used for genome-wide identification and quantification of DNA elements involved in the regulation of gene transcription. Studies that generate multiple high-throughput NGS datasets require data integration methods for two general tasks: 1) generation of genome-wide data tracks representing an aggregate of multiple replicates of the same experiment; and 2) combination of tracks from different experimental types that provide complementary information regarding the location of genomic features such as enhancers. NGS-Integrator is a Java-based command line application, facilitating efficient integration of multiple genome-wide NGS datasets. NGS-Integrator first transforms all input data tracks using the complement of the minimum Bayes’ factor so that all values are expressed in the range [0,1] representing the probability of a true signal given the background noise. Then, NGS-Integrator calculates the joint probability for every genomic position to create an integrated track. We provide examples using real NGS data generated in our laboratory and from the mouse ENCODE database. Our results show that NGS-Integrator is both time- and memory-efficient. Our examples show that NGS-Integrator can integrate information to facilitate downstream analyses that identify functional regulatory domains along the genome.

中文翻译：

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NGS-Integrator：一种有效的工具，可以使用最小的贝叶斯因子来组合多个NGS数据轨道

下一代测序（NGS）已广泛用于全基因组范围内的鉴定和定量涉及基因转录调控的DNA元素。生成多个高通量NGS数据集的研究需要用于两种常规任务的数据集成方法：1）生成代表同一实验的多个重复集合的全基因组数据轨迹；2）来自不同实验类型的轨道的组合，这些轨道提供了有关基因组特征（如增强子）位置的补充信息。NGS-Integrator是基于Java的命令行应用程序，可促进多个基因组范围的NGS数据集的有效集成。NGS-Integrator首先使用最小贝叶斯因子的补码对所有输入数据磁道进行转换，以便所有值都在[0，1]表示在给定背景噪声的情况下真实信号的概率。然后，NGS-Integrator计算每个基因组位置的联合概率，以创建一个整合的轨道。我们提供了使用在实验室中以及从鼠标ENCODE数据库生成的真实NGS数据的示例。我们的结果表明，NGS-Integrator既节省时间又节省内存。我们的例子表明，NGS-Integrator可以整合信息以促进下游分析，从而确定沿基因组的功能性调控域。我们的结果表明，NGS-Integrator既节省时间又节省内存。我们的例子表明，NGS-Integrator可以整合信息以促进下游分析，从而确定沿基因组的功能性调控域。我们的结果表明，NGS-Integrator既节省时间又节省内存。我们的例子表明，NGS-Integrator可以整合信息以促进下游分析，从而确定沿基因组的功能性调控域。