https://github.com/se7en69/ar01-bioarrayexplorer
Microarray Dataset Analysis App offers metadata exploration, counts data analysis, differential expression analysis, and gene set enrichment analysis, providing a user-friendly interface and downloadable results for convenient analysis and sharing.
https://github.com/se7en69/ar01-bioarrayexplorer
Last synced: 4 months ago
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Microarray Dataset Analysis App offers metadata exploration, counts data analysis, differential expression analysis, and gene set enrichment analysis, providing a user-friendly interface and downloadable results for convenient analysis and sharing.
- Host: GitHub
- URL: https://github.com/se7en69/ar01-bioarrayexplorer
- Owner: se7en69
- Created: 2024-02-16T20:37:10.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-02-16T20:38:57.000Z (over 1 year ago)
- Last Synced: 2025-03-18T22:40:35.900Z (7 months ago)
- Language: R
- Size: 14.6 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# AR01-BioArrayExplorer
Microarray Dataset Analysis App offers metadata exploration, counts data analysis, differential expression analysis, and gene set enrichment analysis, providing a user-friendly interface and downloadable results for convenient analysis and sharing.
# Microarray Dataset Analysis App
Welcome to the Microarray Dataset Analysis App! Here's what you can expect:
1. Metadata Exploration
Summary table providing an overview of your dataset metadata.
Two visualization options to analyze variables of interest.
2. Counts Data Analysis
Summary tables and diagnostic scatter plots for insights into the counts data.
Heatmap visualization for gene expression patterns.
PCA plot for dimensionality reduction and clustering analysis.
3. Differential Expression Analysis
Filtered tables of DESeq2 results.
Volcano plot for up- and down-regulated genes.
4. Gene Set Enrichment Analysis
fgsea-based enrichment analysis.
Bar plot of top enriched pathways.
Scatterplot of NES vs. -log(padj).
Option to download filtered results as CSV.
Key Features:
User-friendly interface and downloadable results for convenient analysis and sharing.
Simplify your microarray dataset analysis with our app and uncover valuable insights effortlessly.
Enjoy exploring your data and feel free to contact us with any questions or feedback.
Happy analyzing!