Understand the five processing stages
1. Quality control
Section titled “1. Quality control”QC checks whether the raw reads are plausible before changing them. Use per-sample quality, adapter, duplication, and composition signals to decide whether the run is trustworthy.
2. fastp preprocessing
Section titled “2. fastp preprocessing”fastp removes adapters and low-quality or too-short portions according to the selected cleanup profile. The run preserves preprocessing impact so you can see how many reads survived.
3. Quantification
Section titled “3. Quantification”Salmon estimates transcript abundance efficiently. STAR + featureCounts aligns reads and counts features. The choice affects the count matrix used by DESeq2, so record it when comparing runs.
4. Differential expression with DESeq2
Section titled “4. Differential expression with DESeq2”DESeq2 models count data across groups, estimates dispersion, and tests the configured contrasts. The baseline and design determine the sign and interpretation of log2 fold changes.
5. Optional pathway analysis
Section titled “5. Optional pathway analysis”GSEA and pathway summaries translate ranked gene-level evidence into biological themes. They are downstream of differential-expression statistics and should be interpreted alongside QC and the selected contrast.