NGS Data Analysis: RNA-Seq
Learn to use R to analyse and correctly interpret gene expression levels within various biological contexts:
- Quantify the expression levels of genes in different samples or conditions.
- Identify differentially expressed genes between samples or conditions.
- Identify potential regulatory relationships between genes
- Identify alternative splicing events
Our alumni work at
“
I had a great learning experience and importantly, I was super excited today because I got the opportunity to put my learning to use and I was able to do just that!
Aanuoluwa E.A.
Now in University of Oklahoma
About the Course
About the Course
RNA-Seq is the prime choice for estimating the transcriptome in many biological contexts. Get hands on-experience in RNA-Seq data analysis and interpretation with R. Furthermore, you will be able to identify differentially expressed genes in disease conditions, resolve regulatory pathways and alternative slicing events. In your final project, you will be able to explore RNA expression in cancer and non-cancer patients between different populations. (Data Source: TCGA)
Course Syllabus
Introduction to RNA-Seq
Quality Control and preprocessing RNA-Seq data
Importing and visualisation of RNA-Seq data
Identifying differentially expressed genes (DEGs)
Functional annotation and pathway enrichment
Alternative splicing and isoform detection
Technologies you will use
BaSh
AutoDock
Linux OS
Github
Git
R
NGS Data Analysis: RNA-Seq
100% Practice Oriented
Mentorship
Immediately applicable skills
High quality portfolio projects
Price: $ 100 per month
ENROLL NOWHere is the Plan
Estimated Time
2 weeks
Start by
March 6th
Prerequisites
R, Bash
Real world projects
From industry and academia
Self-paced, flexible learning
Control your learning time and pace
Support for computing
You don't have to buy a new computer to learn
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