This webinar begins with an Introduction to Gene Expression Analysis, where participants will explore the fundamental concepts of transcriptomics and understand how gene expression data drives biological insights. Following this, the RNA-Seq Data Preprocessing and Quality Control session will guide participants through key steps such as data import, quality assessment, and filtering using the Galaxy platform—without the need for coding. The Read Mapping and Quantification module will provide hands-on experience in aligning sequencing reads to reference genomes and quantifying gene expression levels accurately. Next, the Differential Gene Expression Analysis section will focus on identifying significant expression changes across conditions, interpreting statistical results, and visualizing data effectively. Finally, the webinar concludes with a discussion on Functional Annotation and Biological Interpretation, highlighting how to derive meaningful biological insights from gene expression results and exploring the future scope of no-code bioinformatics in research and clinical applications.
Introduction – Overview of gene expression analysis and the Galaxy platform.
Data Input & QC – Importing RNA-Seq data and performing quality checks.
Read Mapping & Quantification – Aligning reads and measuring expression levels.
Differential Expression – Identifying and interpreting gene expression changes.
Functional Annotation – Exploring biological meaning through GO and pathways.
Galaxy Toolkit – Key tools, workflows, and visualization modules.
Applications & Trends – Role of no-code bioinformatics in research and diagnostics.
Key Takeaways – Best practices and workflow optimization tips.
Open Q&A – Addressing participant questions and challenges.
Master Gene Expression Analysis with Galaxy: Impactful Bioinformatics without Code
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