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 ATAC-seq Data: A Complete Beginner’s Guide Part 4: Cell Type Identification
- How to Analyze Single-Cell ATAC-seq Data — A Complete Beginner’s Guide Part 3: Integration and Clustering
- How to Analyze Single-Cell ATAC-seq Data — A Complete Beginner’s Guide Part 2: Thorough Quality Control with Signac
- How to Analyze Single-Cell ATAC-seq Data — A Complete Beginner’s Guide Part 1: From FASTQ to Peaks
Tags
Alternative Splicing Analysis ATAC-seq BAM ChIP-seq chromatin accessibility DESeq2 Differential Expression edgeR FASTQ GATK Mutect2 gene expression GSE282769 heatmap HOMER HPC Isoform limma MACS2 miRNA miRNA-seq MSigDB Normalization peak calling Pixi bioinformatics environment RNA-seq SLURM somatic mutations Transcript VCF whole genome sequencing