nfdata-omics/nanotranseq

Introduction

nfdata-omics/nanotranseq is a Nextflow pipeline for Oxford Nanopore long-read RNA sequencing (direct RNA and cDNA). It takes basecalled FASTQ reads and a reference genome + annotation.

• Long-read QC reports (NanoPlot, toulligQC, FastQC, MultiQC)
• Spliced genome alignments (minimap2) and genome-browser tracks (BigWig)
• Reference-guided transcript assembly (StringTie2)
• Novel transcript and novel isoform discovery (gffcompare)
• Coding-potential classification of novel transcripts / lncRNA calling (CPAT, FEELnc, PLEK consensus)
• Gene- and transcript-level quantification (featureCounts and/or Salmon)
• Differential gene expression (DESeq2)
• Differential transcript usage / isoform switching (DRIMSeq or DEXSeq + IsoformSwitchAnalyzeR)

Pipeline steps

1. Read QC — NanoPlot, toulligQC, FastQC → MultiQC (RAW_READS_QC)
2. Trimming — Chopper, cDNA only (DIRECT_RNA_QC, skipped when --direct_rna)
3. Alignment — minimap2 spliced alignment → sorted BAM (ALIGNMENT); optional GPU via Parabricks
4. Coverage tracks — bedtools + UCSC tools → BigWig (BEDTOOLS_BIGWIG)
5. Assembly + counting — StringTie2 (long-read mode) → StringTie merge → featureCounts (STRINGTIE_FEATURECOUNTS)
6. Novel transcripts — gffcompare vs reference, filter by class code → extract sequences (NOVEL_TRANSCRIPTS)
7. Coding potential — CPAT + FEELnc + PLEK consensus, optional (IDENTIFY_NOVEL_PROTEIN_CODING, --run_coding_potential)
8. Differential expression — DESeq2 (DIFFERENTIAL_ANALYSIS)
9. Pseudo-quantification — Salmon → tximport (PSEUDOALIGNMENT, when --quantification_tool salmon|both)
10. Transcript usage — DRIMSeq/DEXSeq + IsoformSwitchAnalyzeR (TRANSCRIPT_USAGE)

Usage

nextflow run nfdata-omics/nanotranseq \
   -profile <docker/singularity> \
   --input samplesheet.csv \
   --fasta genome.fa \
   --gtf annotation.gtf \
   --outdir results

Samplesheet (--input):

sample,fastq,condition
CTRL_REP1,ctrl1.fastq.gz,control
TREAT_REP1,treat1.fastq.gz,treated

Key parameters:

Param	Default	Notes
--direct_rna	false	true = direct RNA (skips Chopper trimming)
--quantification_tool	featurecounts	featurecounts | salmon | both
--novel_class_codes	u,i,x,j,o	gffcompare classes kept as novel
--run_coding_potential	true	enable CPAT/FEELnc/PLEK
--dtu_tool	drimseq	drimseq | dexseq
--deseq2_formula / --deseq2_comparison / --deseq2_fdr_threshold	—	DE design

Credits

nfdata-omics/nanotranseq was originally written by Karla Alejandra Ruiz Ceja, Leandro Tiburske and Matteo Bonfanti.

Contributions and Support

If you would like to contribute to this pipeline, please see the contributing guidelines.

Citations

If you use this pipeline, please cite the pipeline framework and the tools used in the analysis, including Nextflow, nf-core, NanoPlot, ToulligQC, FastQC, MultiQC, Chopper, minimap2, bedtools, UCSC utilities, StringTie, gffcompare, gffread, CPAT, FEELnc, PLEK, featureCounts/Subread, Salmon, tximport/tximeta, DESeq2, DRIMSeq, DEXSeq and IsoformSwitchAnalyzeR, as applicable to the workflow options enabled in your run. Please also cite the reference genome assembly, transcript annotation and any CPAT training data or pre-built coding-potential models used for the analysis.

An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md file.

This pipeline uses code and infrastructure developed and maintained by the nf-core community, reused here under the MIT license.

The nf-core framework for community-curated bioinformatics pipelines.

Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.

Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.