Rnaseq

nextflow run nf-core/rnaseq -r 3.22.2 -profile test,docker --outdir test_rnaseq

sample,fastq_1,fastq_2,strandedness
CONTROL_REP1,/path/to/ctrl1_R1.fq.gz,/path/to/ctrl1_R2.fq.gz,auto
CONTROL_REP2,/path/to/ctrl2_R1.fq.gz,/path/to/ctrl2_R2.fq.gz,auto
TREATMENT_REP1,/path/to/treat1_R1.fq.gz,/path/to/treat1_R2.fq.gz,auto

nextflow run nf-core/rnaseq -r 3.22.2 -profile docker \
    --input samplesheet.csv --outdir results --genome GRCh38

--fasta /path/to/genome.fa \
--gtf /path/to/annotation.gtf \
--star_index /path/to/star/  # Optional, builds if absent

results/
├── star_salmon/
│   ├── salmon.merged.gene_counts.tsv    # Raw counts for DESeq2
│   ├── salmon.merged.gene_tpm.tsv       # TPM values
│   └── *.bam                            # Alignments
├── multiqc/
│   └── multiqc_report.html              # QC summary
└── pipeline_info/

library(DESeq2)
counts <- read.delim("salmon.merged.gene_counts.tsv", row.names=1)
coldata <- data.frame(
    condition = factor(c("control", "control", "treatment", "treatment"))
)
dds <- DESeqDataSetFromMatrix(
    countData = round(counts),
    colData = coldata,
    design = ~ condition
)
dds <- DESeq(dds)
res <- results(dds, contrast = c("condition", "treatment", "control"))