Tag: heatmap
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How to Cluster RNA-seq Data to Uncover Gene Expression Patterns: Hierarchical and K-means Methods for Absolute Beginners
Introduction: Understanding Clustering in RNA-seq Analysis In the vast landscape of gene expression data, patterns often hide in plain sight. Among thousands of genes measured simultaneously, groups of genes may share similar expression patterns across samples, suggesting coordinated biological functions or responses. Clustering analysis serves as a powerful computational microscope that brings these hidden patterns
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How to Analyze RNAseq Data for Absolute Beginners Part 4: A Complete Guide to Creating Publication-Ready Figures
Introduction After identifying differentially expressed genes (DEGs), the next crucial step is visualizing your results effectively. Strong visualizations don’t just make your data look pretty – they transform complex genomic information into clear, interpretable insights that can reveal hidden patterns and biological stories within your data. In this tutorial, you’ll learn how to create publication-quality
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Recent Posts
- How to Analyze Single-Cell RNA-seq Data – Complete Beginner’s Guide Part 12: Build Gene Co-expression Networks Using hdWGCNA
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- No More Command-Line Only: Run Jupyter Lab, RStudio, and VS Code Interactively in Your Browser on Any HPC Cluster with Pixi
- How to Analyze Single-Cell RNA-seq Data – Complete Beginner’s Guide Part 10: Cell-Cell Communication Analysis Using NicheNet
Tags
Alternative Splicing Analysis ATAC-seq BAM ChIP-seq chromatin accessibility CNV DESeq2 Differential Expression edgeR FASTQ GATK Mutect2 gene expression heatmap HOMER HPC Isoform limma MACS2 MAF miRNA miRNA-seq MSigDB Normalization peak calling RNA-seq SLURM somatic mutations Transcript VCF whole genome sequencing