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所在平台: Udemy |
课程主页: https://www.udemy.com/course/whole-transcriptome-rna-seq-data-analysis-using-linuxr/
课程评论：没有评论
课程名称：使用Linux进行全转录组RNA-Seq数据分析 课程概述：本课程旨在提升您的生物信息学技能，教您如何测量基因的上调和下调情况，即差异基因表达，利用全转录组RNA-Seq数据集。该课程特别适合在分子遗传学与生物信息学交叉领域工作的学生。您将了解到生命科学研究人员为何急需计算技能，哪些类型的生物数据适合进行计算，如何利用Linux/R解决多组学问题，以及生物信息学和计算生物学如何应对现代遗传学的挑战。在不久的将来，生物学家不会仅限于湿实验室的工作，因此请加入我们，使用生物信息学数据科学工具分析、可视化并从您的庞大转录组数据中提取关键信息。这是您从湿实验室向干实验室过渡的最佳途径，帮助您通过Linux命令行界面的bash脚本和R统计软件包分析全转录组NGS数据，并以综合热图的形式可视化结果文件。虽然全球有云计算和商业高性能计算集群设施，但本课程将为您提供如何在有限财务资源下分析多组学数据的见解，而不需要具备丰富的编程专业知识或计算语言知识。
This course will develop your bioinformatics skills that how to measure the up-regulated and down-regulated genes called differential gene expression using whole-transcriptome RNA-Seq dataset. This course is the the best suited to the students working on the boundaries of molecular genetics and bioinformatics. Students will come to know that why life sciences researchers are direly needed computation skills, on which type of biological data computation will apply, how Linux/R compute multi-omics problems, and how bioinformatics and computational biology is evolving to circumvent modern genetics problems.In the time to come, biologists will not restrain to the wet labs only, so let's come and transform yourselves with bioinformatics data science tools for analysis, visualization, and inferring the crux from your big transcriptomic data. So, this is the right stop, that will help you to overwhelm your transition from wet to dry lab and facilitate you to analyze the whole-transcriptome NGS data using bash scripting in Linux command line interface along with R statistical packages for visualizing resultant files in the form of comprehensive heatmap graphs. No doubt there are cloud computing and commercial high performance computing cluster facilities available in the world but this course will provide you the insight that how to analyze multi-omics data with limited financial resources without having much expertise in programming and knowhow to computer languages.
