Goal: Understand structure of nf-file and key concepts (Channels, Processes, Operators)
Reference: https://training.nextflow.io/basic_training/intro/
- practical work through intro (hello_world.nf)
- customisation and adaptation
- add parameters: e.g. params.name ("Hello $name")
- add processes: to print "uname -a and process-ID"
- process directives: - [ ] control processes locally and globally (cpus, memory, container) - [ ] use container from dockerhub (global or process-wise)
- configuration: run on slurm
- workflow on github and test
nextflow run github.com/maxplanck-ie/testflow --params ... -with-apptainer
- Make your selection here: https://pizzamonalisa.de
Goals:
- employ other workflows with singularity, locally and with slurm (queue test)
Challenge: Can we make this work with singularity and slurm?
- Input: basecalled BAM (downsampled, drosophila)
- Output: alignment BAM + QC
- run wf_alignment (dm6) with apptainer (identify approrpiate container)
- Extensions?
- add process (e.g. samtools flagstat)
- send email upon completion
Challenge: Can we predict RNA modifications? (--> m6anet; skip all other analyses)
- Input: samplesheet.csv, pod5/fast5 (subsampled)
- Output: methylation calls: data.result.csv.gz
exchange workflows, test runs & final discussion
module load nextflow/23.10.0
nextflow run -with-apptainer docker://ubuntu:20.04 sources/tutorial.nf
# test runs without modification calling
nextflow run nf-core/nanoseq -profile test,singularity
# couldn't get to work
nextflow run ~/.nextflow/assets/epi2me-labs/wf-alignment --bam data/bam --references /data/repository/organisms/dm6_flybase_r6.12/genome_fasta -with-singularity ontresearch/wf-alignment -without-docker
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video (RNA-seq with salmon) https://www.youtube.com/watch?v=1TbVpMjQUtU
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gitpod: https://gitpod.io/#https://github.com/nextflow-io/training