Introduction to RNA-Seq Analysis

To provide participants with a comprehensive understanding of RNA-Seq analysis, covering the essentials of experimental design, data processing, and the use of bioinformatics tools to analyze gene expression data.

• Introduce RNA-Seq technology and its applications in transcriptomics and genomics.
• Guide participants through RNA-Seq data processing: from raw data to meaningful results.
• Teach the use of computational tools (like R, Bioconductor) for differential expression analysis and visualization.
• Help participants interpret RNA-Seq results for biological insights such as gene expression patterns and functional pathways.
• Build skills in using RNA-Seq data to drive research and clinical applications in genomics and molecular biology.

• Researchers and students in bioinformatics, molecular biology, and genomics.
• Bioinformatics enthusiasts looking to deepen their understanding of RNA-Seq analysis.
• Healthcare professionals and clinicians with an interest in genomic data analysis.
• Basic programming knowledge (preferably in R) is recommended but not required for beginners.

• Understand the basics of RNA-Seq technology and its role in gene expression analysis.
• Be able to process and analyze RNA-Seq data, including data cleaning, alignment, and normalization.
• Perform differential expression analysis and visualize results using bioinformatics tools such as R and DESeq2.
• Interpret biological significance of RNA-Seq results in the context of gene expression and functional genomics.
• Apply RNA-Seq data analysis techniques in real-world research or clinical studies.