44 lines
1.8 KiB
Markdown
44 lines
1.8 KiB
Markdown
# RNA-seq DESeq2 Pipeline
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A sequential Kubernetes Job pipeline for differential expression analysis on yeast RNA-seq data. Each stage runs as a one-shot Job against a shared PVC, in order.
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## Dataset
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- Source: Gierliński et al., ENA accession PRJEB5348
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- Reads: 50bp single-end
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- Conditions: wild-type (WT: ERR458493–495) vs. snf2 deletion mutant (snf2: ERR458500–502)
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## Pipeline stages
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| Order | File | Stage |
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|---|---|---|
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| 1 | `01-pvc.yaml` | Shared PersistentVolumeClaim for pipeline data and intermediate files |
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| 2 | `02-job-sra-download.yaml` | Downloads raw FASTQ reads from SRA/ENA |
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| 2b | `02b-job-sra-download-extra.yaml` | Downloads the remaining replicate samples |
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| 3 | `03-job-fastqc.yaml` | FastQC read quality control |
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| 4 | `04-job-star.yaml` | STAR alignment to the reference genome |
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| 4b | `04b-job-star-extra.yaml` | STAR alignment for the remaining replicate samples |
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| 5 | `05-job-featurecounts.yaml` | Gene-level count matrix from aligned reads |
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| 6 | `06-job-deseq2.yaml` | DESeq2 differential expression analysis (WT vs. snf2) |
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## Results
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- STAR alignment: ~85–90% mapping rate across samples
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- DESeq2 output visualized (volcano plot, etc.) in a Jupyter R notebook
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## Running
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Namespace: `rnaseq`. Jobs are sequential — each depends on the previous stage's output landing on the shared PVC, so apply and wait for completion before moving to the next:
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```bash
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kubectl apply -f 01-pvc.yaml
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kubectl apply -f 02-job-sra-download.yaml
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kubectl get jobs -n rnaseq -w # wait for Completed before continuing
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kubectl apply -f 02b-job-sra-download-extra.yaml
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kubectl apply -f 03-job-fastqc.yaml
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kubectl apply -f 04-job-star.yaml
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kubectl apply -f 04b-job-star-extra.yaml
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kubectl apply -f 05-job-featurecounts.yaml
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kubectl apply -f 06-job-deseq2.yaml
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```
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