From Reads to Result Reference VS Denovo RNA Seq
From Reads to Results: Reference vs. De Novo RNA-Seq The Ultimate Guide to Mastering Transcriptome Assembly and Differential Gene Expression
Course Description
In the era of Big Data Genomics, understanding how to process Next-Generation Sequencing (NGS) data is a critical skill for any life scientist. This course provides an end-to-end deep dive into RNA-Seq analysis, comparing the high-precision Reference-Based workflow with the complex, "from-scratch" De Novo Assembly approach. You will learn to navigate the command-line interface to perform quality control, read mapping, and transcript reconstruction. Beyond traditional pipelines, we explore how AI and Machine Learning (ML) are revolutionizing gene expression estimation and isoform discovery. By the end of this course, you will be able to transform millions of raw FASTQ reads into statistically significant results and professional-grade visualizations, ready for publication or clinical application.
What You'll Learn
The fundamental differences between Reference-Guided and De Novo workflows.
How to perform rigorous Quality Control (QC) and adapter trimming on raw reads.
Mastering alignment tools like HISAT2 and STAR for model organisms.
Assembling transcriptomes for non-model species using Trinity.
Utilizing AI algorithms for feature selection and batch effect removal.
Conducting Differential Gene Expression (DGE) analysis with DESeq2 and EdgeR.
Functional annotation and Gene Ontology (GO) enrichment.
Curriculum
No modules added yet.
