Differential Gene Expression Analysis By R
Bioinformatics, R Studio, Galaxy, NGS, RNA-Seq analysis, Biological Sciences, Transcriptional Profiling
Ratings 1.94 / 5.00
What You Will Learn!
- Extract the data from online database repository for NGS analysis
- Galaxy tools for RNA-Seq analysis
- Differential Expression analysis by R
- All steps of RNA-Seq analysis
Description
In recent years, RNA sequencing (in short RNA-Seq) has become a very widely used technology to analyze the continuously changing cellular transcriptome, i.e. the set of all RNA molecules in one cell or a population of cells. One of the most common aims of RNA-Seq is the profiling of gene expression by identifying genes or molecular pathways that are differentially expressed (DE) between two or more biological conditions.
This course is actually introducing RNA-Seq analysis. After this course, you will be able to do a complete analysis of biomedical data by galaxy and R. In this course, you will learn analysis for differential gene expression by RNA-Seq analysis. How to use R and RStudio for Bioinformatics. Code and slides of this course will help you to do analysis of RNA-Seq analysis. You will be able to know the PCA, box plot graphs, histograms, and heat map.
The original data are available at NCBI Gene Expression Omnibus (GEO) under accession number GSE52194. The raw RNA-Seq reads have been extracted from the Sequence Read Archive (SRA) files and converted into FASTQ files. In summary, this course has been designed for all skill levels and even if you have no programming or statistical background you will be successful in this course!
Who Should Attend!
- Beginners Bioinformatics curious about NGS analysis
