Quinlan Aaron R
Department of Public Health Sciences, Center for Public Health Genomics, Department of Biochemistry and Molecular Genetics, and Department of Computer Science. University of Virginia, Charlottesville, Virginia.
Curr Protoc Bioinformatics. 2014 Sep 8;47:11.12.1-34. doi: 10.1002/0471250953.bi1112s47.
Technological advances have enabled the use of DNA sequencing as a flexible tool to characterize genetic variation and to measure the activity of diverse cellular phenomena such as gene isoform expression and transcription factor binding. Extracting biological insight from the experiments enabled by these advances demands the analysis of large, multi-dimensional datasets. This unit describes the use of the BEDTools toolkit for the exploration of high-throughput genomics datasets. Several protocols are presented for common genomic analyses, demonstrating how simple BEDTools operations may be combined to create bespoke pipelines addressing complex questions.
技术进步使得DNA测序能够作为一种灵活的工具来表征遗传变异,并测量各种细胞现象的活性,如基因异构体表达和转录因子结合。从这些进步所促成的实验中提取生物学见解需要分析大型多维数据集。本单元介绍了使用BEDTools工具包来探索高通量基因组数据集。文中给出了几个用于常见基因组分析的方案,展示了如何将简单的BEDTools操作组合起来,以创建解决复杂问题的定制流程。