【背景】随着测序费用的降低,越来越多的科学家选择利用高通量测序技术研究噬菌体的基因组序列。通过对这些基因组数据的分析和研究,一些科学家也开发出了判断dsDNA噬菌体末端序列的方法,但这些方法是基于Linux系统下的命令,并没有在Windows操作系统下的软件。【目的】在Windows平台下开发一款免费的、可以在高通量测序获得的庞大序列文件中找到dsDNA噬菌体基因组末端序列的软件PhageGT。【方法】使用Visual Studio 2019开发一个基于对话框的微软基础类库(Microsoft Foundation Classes,MFC)应用程序。软件使用C++语言开发,逐行读取序列文件中的每条Reads,并设计相应的算法进行统计、计算。【结果】软件PhageGT可在高通量测序文件中提取出不同序列出现的频率、排序,并利用提取序列的最高频率和序列平均频率的比值(R值)判断噬菌体基因组是否存在末端序列。【结论】软件PhageGT的使用比较方便、简单。软件PhageGT和本文所利用的所有测试数据均可从https://zenodo.org/record/4674231#.YHADb-gzZxc免费获得。 相似文献
Due to the technological advances, it has been well-established that obesity is strongly correlated with various health problems. Among these problems, dyslipidemia is one of the most important concomitant symptoms under obese status which is the main driving force behind the pathological progression of cardio-metabolic disorder diseases. Importantly, the type of dyslipidemia, arising from concerted action of obesity, has been identified as “metabolic related dyslipidemia”, which is characterized by increased circulating levels of Low density lipoprotein cholesterol (LDL-C), Triglycerides (TG) accompanied by lower circulating levels of High density lipoprotein cholesterol (HDL-C). On the other hand, the metabolic related dyslipidemia is being verified as a vital link between obesity and hypertension, diabetes mellitus, and Cardiovascular disease (CVD). In this review, we summarized the current understanding of metabolic related dyslipidemia and the potential mechanisms which lead to the pathogenesis of obesity. Meanwhile, we also summarized the emerging results which focused on several novel lipid bio-markers in metabolic related dyslipidemia, such as pro-protein convertase subtilisin/kexin type 9 (PCSK9) and sphingosine-1-phosphate (S1P), and their potential use as biomarkers of metabolic related dyslipidemia.