RNA-Seq Data Analysis Guide 🧬📊

RNA-Seq is a powerful technique for analyzing gene expression. Below is a step-by-step guide to help you through the process:

1. Workflow Overview

The RNA-Seq workflow typically includes:

• Sample Preparation 🧪
  • RNA extraction
  • Library construction
• Sequencing 📡
  • High-throughput sequencing (e.g., Illumina)
• Data Analysis 📊
  • Alignment to reference genome
  • Variant calling
  • Differential expression analysis

2. Key Tools & Software

• Aligners: Bowtie, TopHat
• Analysis Pipelines: STAR, Salmon
• Visualization: IGV (Interactive Genomics Viewer)

3. Best Practices

• Always perform quality control before alignment 🧾
  • Use FastQC for read quality assessment
• Consider normalization steps for accurate comparisons ⚖️
• Explore our bioinformatics tools guide for more resources 🔍

RNA seq workflow

4. Common Challenges

• Low mapping efficiency 📉
• Bias in coverage ⚠️
• Noise in expression data 🧼

For advanced techniques, check out our RNA-Seq troubleshooting guide. 📚