wf-transcriptomes-v202/docs/quickstart.md

Quickstart

The workflow uses nextflow to manage compute and software resources, as such nextflow will need to be installed before attempting to run the workflow.

The workflow can currently be run using either Docker, Singularity or conda to provide isolation of the required software. Each method is automated out-of-the-box provided either docker, singularity or conda is installed.

It is not required to clone or download the git repository in order to run the workflow. For more information on running EPI2ME Labs workflows visit out website.

Workflow options

To obtain the workflow, having installed nextflow, users can run:

nextflow run epi2me-labs/wf-isoforms --help

to see the options for the workflow.

Example execution of a workflow for reference-based transcript assembly

This example uses a synthetic SIRV dataset, so we need to tell minimap2 about the non-canonical splice junctions with --minimap2_opts '-uf --splice-flank=no'

OUTPUT=~/output;
nextflow run wf-isoforms/ --fastq test_data/fastq  --ref_genome test_data/SIRV_150601a.fasta --ref_annotation test_data/SIRV_isofroms.gtf
--minimap2_opts '-uf --splice-flank=no' --out_dir outdir -w workspace_dir -profile conda -resume

# To evaluate the workflow on a larger Drosophila dataset
./evaluation/run_evaluation_dmel.sh outdir

Example workflow for denovo transcript assembly

OUTPUT=~/output
nextflow run . --fastq test_data/fastq --denovo --ref_genome test_data/SIRV_150601a.fasta  -profile local --out_dir ${OUTPUT} -w ${OUTPUT}/workspace \
--sample sample_id -resume

A full list of options can be seen in nextflow_schema.json. Below are some commonly used ones.

• Threshold for including isoforms into interactive table transcript_table_cov_thresh = 50
• Run the denovo pipeline denovo = true (default false)
• To run the workflow with direct RNA reads --direct_rna (skips the pychopper step).

Pychopper and minimap2 can take options via minimap2_opts and pychopper_opts, for example:

• When using the SIRV synthetic test data
  • minimap2_opts = '-uf --splice-flank=no'
• pychopper needs to know which cDNA synthesis kit used
  • SQK-PCS109: use pychopper_opts = '-k PCS109' (default)
  • SQK-PCS110: use pychopper_opts = '-k PCS110'
• pychopper can use one of two available backends for identifying primers in the raw reads
  • nhmmscan pychopper opts = '-m phmm'
  • edlib pychopper opts = '-m edlib'

Note: edlib is set by default in the config as it's quite a lot faster. However it may be less sensitive than nhmmscan.