Abstract：Abstract: The differential expression analysis is one of the core objectives of transcriptome research, which is of great significance to reveal the gene function and regulation rules. However, the analysis is a multi-step iteration with a time-consuming and computationally intensive process. There are complex data dependencies between software, and the input and output formats are not the same. In the traditional way, the complex installation and use of software, tedious manual operation and difficult migration of analysis environment are the key problems to be solved. In view of the above problems, an efficient and automated method for transcriptome differential expression analysis was proposed. For the first time, Docker container technology, an open source cloud project, was applied in the field of biological information. First of all, the best practice process was embedded and integrated in Docker container. Then the multi-script interaction and web services were combined, and eventually, a “black box” of lightweight, portable, and highly automated transcriptome differential expression analysis was formed. Experimental results showed that, compared with the traditional method, this method reduced the analysis time by about 72%, and improved the efficiency more than twice. Therefore, the method may provide more efficient technical support for researchers.
引用本文:
赵 芳, 高 静, 刘振羽, 王永军, 邬学敏. 一种高效自动化的转录组差异性表达分析方法[J]. 生命科学研究, 2019, 23(1): 39-45. ZHAO Fang, GAO Jing, LIU Zhen-yu, WANG Yong-jun, WU Xue-min. A Highly Efficient and Automated Method for Differential Expression Analysis of Transcriptome. Life Science Research, 2019, 23(1): 39-45.
