RNA-Seq is an exciting and in-demand next-generation sequencing (NGS) method used for identifying genes and pathways underlying particular diseases or conditions.

As high-throughput sequencing becomes more affordable and accessible to a wider community of researchers, the knowledge to analyze this data is becoming an increasingly valuable skill, especially for those who are still in Bachelors, Masters or even Doctoral degrees.

Get yourself enrolled in this in-demand course and learn industrial level RNA-seq workflow and analysis, leading to skills in discovering differentially expressed genes and biological processes which might be important for your condition of interest!

The course starts from the very basics of Next Generation Sequencing, the basics of sequencing and how the raw data is produced, then a detailed overall overview is given of the RNA-Seq workflow with an emphasis on differential expression (DE) analysis.

The course further covers; how to prepare data for RNA-seq analysis, do quality control and trimming, process the data for mapping against the reference genome, leading to quantification of raw reads for each gene, assess the quality of the count data, and identify outliers and detect major sources of variation in the data.

Finally, you will learn how to use DESeq2 to model the reads count data using a negative binomial model and test for differentially expressed genes. Visualization of the results with heatmaps and volcano plots will be performed and the significant differentially expressed genes will be identified and saved, ending with Gene Ontology and Pathway Analysis.