TieBrush: an efficient method for aggregating and summarizing mapped reads across large datasets
TieBrush: an efficient method for aggregating and summarizing mapped reads across large datasets
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DOI：
10.1093/bioinformatics/btab342
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发表时间：
2021-05-08
期刊：
影响因子：
5.8
通讯作者：
Pertea, Mihaela
中科院分区：
文献类型：
--
作者：
Varabyou, Ales;Pertea, Geo;Pertea, Mihaela
尽管以编程方式总结和视觉检查测序数据的能力是基因组分析的组成部分，但目前可用的方法不能处理大量样品。特别是，在两组数千个RNA-seq样本之间进行转录景观的视觉比较受到可用计算资源的限制，由于数据的庞大规模，这些计算资源可能会不堪重负。在这项工作中，我们提出了TieBrush，一个软件包，旨在处理非常大的测序数据集（RNA，全基因组，外显子组等）。转换成一种能够快速进行视觉和计算检查的形式。TieBrush还可以用作聚合下游计算分析数据的方法，并且与大多数将对齐读段作为输入的软件工具兼容。
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.