Whole Transcriptome RNA-Seq Data Analysis using Linux
"softddl.org"
18-01-2022, 04:48
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MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 7 lectures (2h 54m) | Size: 1.88 GB
Differential Gene Expression Analysis
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 7 lectures (2h 54m) | Size: 1.88 GB
Differential Gene Expression Analysis
What you'll learn
Differential Gene Expression Analysis
Linux CLI Bash Scripting
RNA-Seq Data Analysis
NGS databases and used software in the pipeline
Requirements
Installation of Linux/R
Description
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.
Who this course is for
University students/Freelancers working in medicine research, biotech & bioinformatics industry
Homepage
https://www.udemy.com/course/whole-transcriptome-rna-seq-data-analysis-using-linuxr/
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