wf-transcriptomes-v202/docs/intro.md

Introduction

This workflow identifies RNA isoforms using either cDNA or direct RNA (dRNA) Oxford Nanopore reads.

Preprocesing

cDNA reads are initially preprocessed by pychopper for the identification of full-length reads, as well as trimming and orientation correction (This step is omitted for direct RNA reads).

Reference-aided approach

• Full length reads are mapped to a supplied reference genome using minimap2
• Transcripts are assembled by stringtie in long read mode (with or without a guide reference annotation) to generate the GFF annotation.
• The annotation generated by the pipeline is compared to the reference annotation. using gffcompare

de novo-based approach (experimental!)

• Sequence clusters are generated using isONclust2
  • If a reference genome is supplied, cluster quality metrics are determined by comparing
    with clusters generated from a minimap2 alignment.
• A consensus sequence for each cluster is generated using spoa
• Three rounds of polishing using racon and minimap2 to give a final polished CDS for each gene.
• Full-length reads are then mapped to these polished CDS.
• Transcripts are assembled by stringtie as for the reference-based approach.
• Note: This approach is currently not supported with direct RNA reads.

Workflow inputs

• Directory containing cDNA/direct RNA reads. Or a directory containing subdirectories each with reads from different samples (in fastq/fastq.gz format)
• Reference genome in fasta format (required for reference-based assembly).
• Optional reference annotation in GFF2/3 format.