nf-core/hmfrnaseq

Introduction

nf-core/hmfrnaseq is a bioinformatics pipeline for RNA-seq analysis integrating WiGiTS tools developed by the Hartwig Medical Foundation. It accepts paired-end Illumina FASTQ files or pre-aligned BAM files as input. The pipeline performs read alignment, quality control (including rRNA contamination checks), and uses Isofox for transcript quantification, alternative splicing detection, and fusion calling. Results are summarised in per-sample and aggregated MultiQC reports.

Pipeline flowchart (click to expand)

flowchart LR
    subgraph Input
        FASTQ[FASTQ / BAM]
    end

    subgraph QC
        FASTQC[FastQC]
    end

    subgraph Alignment
        STAR[STAR] --> SORT[SAMtools Sort] --> MERGE[Sambamba Merge] --> MARKDUP[MarkDuplicates]
    end

    subgraph "RNA QC (parallel)"
        RUSTQC[RustQC]
        RSEQC[RSeQC split_bam]
    end

    subgraph Analysis
        ISOFOX[Isofox]
    end

    subgraph Reports
        MULTIQC[MultiQC]
    end

    FASTQ --> FASTQC
    FASTQ --> STAR
    MARKDUP --> RUSTQC
    MARKDUP --> RSEQC
    MARKDUP --> ISOFOX
    RUSTQC --> MULTIQC
    RSEQC --> MULTIQC
    FASTQC --> MULTIQC
    ISOFOX --> MULTIQC

Loading

The flowchart above shows the default workflow. A FastQC-only mode is also available via --mode fastqc_workflow (runs FastQC on the raw reads, then stops — no alignment or downstream analysis).

1. Read QC (FastQC)
2. Alignment (STAR)
3. BAM processing (SAMtools, Sambamba)
4. Duplicate marking (GATK MarkDuplicates)
5. RNA QC and rRNA content (RustQC, RSeQC) — run in parallel with Isofox
6. Transcript quantification and fusion detection (Isofox)
7. QC report (MultiQC)

A FastQC-only mode is also available (--mode fastqc_workflow), which runs step 1 and stops.

Usage

Note

If you are new to Nextflow and nf-core, please refer to this page on how to set-up Nextflow. Make sure to test your setup with -profile test before running the workflow on actual data.

First, prepare a samplesheet with your input data that looks as follows:

samplesheet.csv:

group_id,subject_id,sample_id,sample_type,sequence_type,filetype,info,filepath
SAMPLE1,SUBJECT1,SAMPLE1_T,tumor,rna,fastq,library_id:LIB001;lane:L001,/path/to/R1.fastq.gz;/path/to/R2.fastq.gz

Each row represents a pair of FASTQ files for one lane. For samples sequenced across multiple lanes, add one row per lane with the same identifiers.

Now, you can run the pipeline using:

nextflow run nf-core/hmfrnaseq \
   -profile <docker/singularity/.../institute> \
   --input samplesheet.csv \
   --outdir <OUTDIR> \
   --genome GRCh38_hmf

Warning

Please provide pipeline parameters via the CLI or Nextflow -params-file option. Custom config files including those provided by the -c Nextflow option can be used to provide any configuration except for parameters; see docs.

Credits

nf-core/hmfrnaseq was originally written by Rayan Hassaine.

Thank you the Hartwig Medical Foundation for developing the WiGiTS tools integrated in this pipeline.

Contributions and Support

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

Citations

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.