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A pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq

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nf-core/denovotranscript

GitHub Actions CI Status GitHub Actions Linting StatusAWS CICite with Zenodo nf-test

Nextflow run with conda run with docker run with singularity Launch on Seqera Platform

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Introduction

nf-core/denovotranscript is a bioinformatics pipeline for de novo transcriptome assembly of paired-end short reads from bulk RNA-seq. It takes a samplesheet and FASTQ files as input, perfoms quality control (QC), trimming, assembly, redundancy reduction, pseudoalignment, and quantification. It outputs a transcriptome assembly FASTA file, a transcript abundance TSV file, and a MultiQC report with assembly quality and read QC metrics.

nf-core/transfuse metro map

  1. Read QC of raw reads (FastQC)

  2. Adapter and quality trimming (fastp)

  3. Read QC of trimmed reads (FastQC)

  4. Remove rRNA or mitochondrial DNA (optional) (SortMeRNA)

  5. Transcriptome assembly using any combination of the following:

    • Trinity with normalised reads (default=True)
    • Trinity with non-normalised reads
    • rnaSPAdes medium filtered transcripts outputted (default=True)
    • rnaSPAdes soft filtered transcripts outputted
    • rnaSPAdes hard filtered transcripts outputted
  6. Redundancy reduction with Evidential Gene tr2aacds. A transcript to gene mapping is produced from Evidential Gene's outputs using gawk.

  7. Assembly completeness QC (BUSCO)

  8. Other assembly quality metrics (rnaQUAST)

  9. Transcriptome quality assessment with TransRate, including the use of reads for assembly evaluation. This step is not performed if profile is set to conda or mamba.

  10. Pseudo-alignment and quantification (Salmon)

  11. HTML report for raw reads, trimmed reads, BUSCO, and Salmon (MultiQC)

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:

sample,fastq_1,fastq_2
CONTROL_REP1,AEG588A1_S1_L002_R1_001.fastq.gz,AEG588A1_S1_L002_R2_001.fastq.gz

Each row represents a pair of fastq files (paired end).

Now, you can run the pipeline using:

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

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.

For more details and further functionality, please refer to the usage documentation and the parameter documentation.

Pipeline output

To see the results of an example test run with a full size dataset refer to the results tab on the nf-core website pipeline page. For more details about the output files and reports, please refer to the output documentation.

Credits

nf-core/denovotranscript was written by Avani Bhojwani (@avani-bhojwani) and Timothy Little (@timslittle).

Contributions and Support

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

For further information or help, don't hesitate to get in touch on the Slack #denovotranscript channel (you can join with this invite).

Citations

If you use nf-core/denovotranscript for your analysis, please cite it using the following doi: 10.5281/zenodo.13324371

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

You can cite the nf-core publication as follows:

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.