Pipeline Chaining: RNA-seq → Differential Abundance

examples/04 - RNA-seq to DifferentialAbundance.json

This workflow demonstrates chaining nf-core/rnaseq and nf-core/differentialabundance pipelines together.

The workflow launches nf-core/rnaseq with a user-provided samplesheet and monitors its execution. When RNA-seq completes successfully, it automatically constructs file paths to the output count matrices (salmon.merged.gene_counts.tsv and salmon.merged.gene_lengths.tsv) and launches nf-core/differentialabundance with these files as inputs.

The output directory is automatically generated from the CSV filename, and all parameters are configured via a single function node at the start.

Setup

This workflow comes pre-configured with test data and works out of the box!

• All Seqera nodes need a Seqera configuration to be assigned
• Two Launchpad entries are required: nf-core-rnaseq and nf-core-differentialabundance
• Open the "Set user inputs" function node to configure file paths
• The workflow uses small test data from this repository: S. cerevisiae (yeast) RNA-seq with ~7 samples

Test files (GitHub-hosted):

• Samplesheet: docs/examples/data/rnaseq-tests-datasets.csv - includes sample, fastq_1, fastq_2, strandedness, treatment, and replicate columns
• Contrasts: docs/examples/data/rnaseq-test-contrasts.csv - defines comparisons like WT vs RAP1_UNINDUCED
• Genome: R64-1-1 (S. cerevisiae from iGenomes)

To use your own data, edit the function node:

• Set msg.rnaseqSamplesheet to your samplesheet path (must include a grouping column like treatment or group)
• Set msg.contrastsCSV to your contrasts file
• Set msg.basePath to your output location (e.g., s3://my-bucket/results)
• Set msg.genome or provide explicit msg.gtfFile and msg.fasta paths