📋 Workflow
Full workflow, products add-to-cart directly1
Raw data QC
1 hCheck read quality, adapters and contamination, filter low-quality reads
💡 Tip Inspect quality scores and GC distribution
⚠️ Caution Unremoved adapters skew alignment
🧪 Materials for this step (click to shop by spec/brand)
2
Alignment and quantification
1–2 daysAlign filtered reads to reference genome and quantify gene/transcript expression
💡 Tip Choose aligner per species and data type
⚠️ Caution Proper parameters avoid multi-mapping bias
🧪 Materials for this step (click to shop by spec/brand)
3
Differential expression and statistics
1 dayIdentify differential genes with statistical models and correct for multiple testing
💡 Tip Correct batch effects
⚠️ Caution Sample size/design affect power
🧪 Materials for this step (click to shop by spec/brand)
4
Enrichment and visualization
1 dayRun pathway enrichment and visualize with volcano plots, heatmaps etc.
💡 Tip Multiple databases improve enrichment
⚠️ Caution Interpret with experimental context
🧪 Materials for this step (click to shop by spec/brand)
⚠️ 5 Common Beginner Mistakes
- ① Insufficient QC biases downstream
- ② Improper alignment/quantification parameters
- ③ Uncorrected batch masks differences
- ④ Uncorrected multiple testing gives false positives
- ⑤ Over-interpretation without validation
❓ FAQ
+Most common analysis tools?
FastQC for QC, STAR for alignment, edgeR/DESeq2 for DE, Seurat for single-cell etc.
+How to handle high-throughput data?
Use HPC/cluster and standardized pipelines for parallel processing.
+How to ensure reproducibility?
Document versions/parameters, use pipelines (Snakemake/Nextflow), share scripts.