Bulk RNA-Seq Analysis
Description
Embark on a comprehensive journey into RNA sequencing (RNA-Seq) analysis with our intensive workshop tailored for researchers, bioinformaticians, and data scientists eager to master this powerful genomic technique. RNA-Seq has transformed our understanding of transcriptomics, offering unparalleled insights into gene expression patterns and regulatory mechanisms across diverse biological systems.
In this workshop, you’ll explore the core principles and advanced methodologies of RNA-Seq analysis, covering everything from raw data processing and quality assessment to differential expression analysis and functional interpretation. Through a combination of lectures, guided tutorials, and hands-on exercises, you’ll develop the skills to analyze and interpret RNA-Seq data using industry-standard tools such as DESeq2, edgeR, and GSEA.
Key Highlights:
Introduction to RNA-Seq
- Understand the principles and applications of RNA sequencing technology
- Compare RNA-Seq to other gene expression analysis methods
Raw Data Processing and Quality Control
- Assess the quality of raw sequencing data using FastQC
- Perform read trimming and filtering to improve data quality
Read Alignment and Quantification
- Align reads to a reference genome using popular tools like HISAT2 or STAR
- Quantify gene expression levels using tools such as featureCounts or Salmon
Data Normalization and Batch Effect Correction
- Apply various normalization methods (e.g., TPM, RPKM, DESeq2’s median of ratios)
- Identify and correct for batch effects using tools like ComBat or SVA
Exploratory Data Analysis
- Perform and interpret principal component analysis (PCA) on RNA-Seq data
- Create and analyze sample-to-sample correlation heatmaps
Differential Expression Analysis
- Conduct differential expression analysis using DESeq2 or edgeR
- Interpret volcano plots and MA plots to visualize differential expression results
Functional Enrichment Analysis
- Perform Gene Ontology (GO) and pathway enrichment analysis
- Visualize enrichment results using tools like Enrichr or g:Profiler
Advanced Analysis Techniques
- Explore gene co-expression networks
- Conduct gene set enrichment analysis (GSEA) for hypothesis testing
Who Should Attend: .
This workshop is perfect for molecular biologists, geneticists, bioinformaticians, and any researchers interested in transcriptome analysis and functional genomics.
Harness the full potential of RNA-Seq to unravel the complexities of gene expression. Join us for this in-depth workshop and elevate your genomic data analysis capabilities to new heights!