TieBrush：一种跨大型数据集聚合和汇总比对读段的有效方法。
TieBrush: an efficient method for aggregating and summarizing mapped reads across large datasets.
作者信息
Varabyou Ales, Pertea Geo, Pockrandt Christopher, Pertea Mihaela
机构信息
Center for Computational Biology, Johns Hopkins University, Baltimore, MD 21211, USA.
Department of Computer Science, Johns Hopkins University, Baltimore, MD 21211, USA.
出版信息
Bioinformatics. 2021 Oct 25;37(20):3650-3651. doi: 10.1093/bioinformatics/btab342.
SUMMARY
Although the ability to programmatically summarize and visually inspect sequencing data is an integral part of genome analysis, currently available methods are not capable of handling large numbers of samples. In particular, making a visual comparison of transcriptional landscapes between two sets of thousands of RNA-seq samples is limited by available computational resources, which can be overwhelmed due to the sheer size of the data. In this work, we present TieBrush, a software package designed to process very large sequencing datasets (RNA, whole-genome, exome, etc.) into a form that enables quick visual and computational inspection. TieBrush can also be used as a method for aggregating data for downstream computational analysis, and is compatible with most software tools that take aligned reads as input.
AVAILABILITY AND IMPLEMENTATION
TieBrush is provided as a C++ package under the MIT License. Precompiled binaries, source code and example data are available on GitHub (https://github.com/alevar/tiebrush).
SUPPLEMENTARY INFORMATION
Supplementary data are available at Bioinformatics online.
摘要
尽管以编程方式总结和可视化检查测序数据的能力是基因组分析的一个组成部分，但目前可用的方法无法处理大量样本。特别是，对两组数千个RNA-seq样本之间的转录图谱进行可视化比较受到可用计算资源的限制，由于数据量巨大，这些资源可能会不堪重负。在这项工作中，我们展示了TieBrush，这是一个软件包，旨在将非常大的测序数据集（RNA、全基因组、外显子组等）处理成一种能够进行快速可视化和计算检查的形式。TieBrush还可以用作汇总数据以进行下游计算分析的方法，并且与大多数将比对读数作为输入的软件工具兼容。
可用性和实现方式
TieBrush以C++包的形式根据MIT许可提供。预编译的二进制文件、源代码和示例数据可在GitHub（https://github.com/alevar/tiebrush）上获取。
补充信息
补充数据可在《生物信息学》在线版上获取。
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