Differential Gene Expression Analysis using GEO2R: An Interactive Webtool
Skills you will gain:
About Workshop:
This bioinformatics study aimed to identify differentially expressed genes (DEGs), and the rapid development and extensive application of gene expression profile data has led to bioinformatics analysis becoming a popular method to explore disease pathogenesis. Bioinformatics analysis provides significant insight into the pathophysiological mechanisms of diseases at the genetic level. At this junction, the R language is used to identify DEGs through Bioconductor packages to show all DEGs by generating the volcano map, Euclidean distances to perform clustering, Venn diagram, and heatmap.
Aim: The aim of DGE analyses is the identification of genes showing significant differences in expression levels between two or more groups.
Workshop Objectives:
- To determine if the gene differences in expression between groups are significant given
the amount of variation within groups or between the biological replicates. - To compare two or more groups of samples to identify genes that are
differentially expressed across experimental conditions.
What you will learn?
Day 1: GEO repository and GEO2R web tool.
- General Overview of GEO, Data Organization, Query, and Analysis.
- Overview of GEO2R, how to use, Edit options and features, Limitations and caveats, Summary Statistics.
Day 2: R studio and Bioconductor packages.
- R studio and Bioconductor packages installation.
- DESeq2, GEOquery, and limma Bioconductor package.
Day 3: DGE Analysis with RNA-seq Data and Microarray Data.
- Differential expression analysis with DESeq2 for RNA-seq Analysis.
- Differential expression analysis with GEOquery and limma for Microarray data analysis.
Mentor Profile
Fee Plan
Important Dates
03 Oct 2024 Indian Standard Timing 07:00 PM
03 Oct 2024 to 05 Oct 2024 Indian Standard Timing 08:00 PM
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Intended For :
- Undergraduate degree in Life Sciences, Biotechnology, Bioinformatics, or related fields.
- Researchers and professionals in genomics, molecular biology, and bioinformatics.
- Individuals with a keen interest in gene expression analysis and computational biology.
Career Supporting Skills
Workshop Outcomes
- Proficiency in using GEO2R for differential gene expression analysis.
- Ability to interpret and validate gene expression data.
- Understanding of key bioinformatics concepts related to gene expression.
- Skills in data retrieval, normalization, and visualization.
- Preparedness for advanced research and career opportunities in genomics.
