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nf-core/viralgenie

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

GitHub Actions CI Status GitHub Actions Linting Status

Tip

Make sure to checkout the viralgenie website for more elaborate documentation!

Introduction

Viralgenie is a bioinformatics best-practice analysis pipeline for reconstructing consensus genomes and to identify intra-host variants from metagenomic sequencing data or enriched based sequencing data like hybrid capture.

Pipeline summary

viralgenie-workflow

  1. Read QC (FastQC)
  2. Performs optional read pre-processing
  3. Metagenomic diveristy mapping
    • Performs taxonomic classification and/or profiling using one or more of:
    • Plotting Kraken2 and Kaiju (Krona)
  4. Denovo assembly (SPAdes, TRINITY, megahit), combine contigs.
  5. [Optional] extend the contigs with sspace_basic and filter with prinseq++
  6. Contig reference idententification (blastn)
    • Identify top 5 blast hits
    • Merge blast hit and all contigs of a sample
  7. [Optional] Precluster contigs based on taxonomy
    • Identify taxonomy Kraken2 and\or Kaiju
    • Resolve potential inconsistencies in taxonomy & taxon filtering | simplification bin/extract_precluster.py
  8. Cluster contigs (or every taxonomic bin) of samples, options are:
  9. Scaffolding of contigs to centroid (Minimap2, iVar-consensus)
  10. [Optional] Annotate 0-depth regions with external reference bin/lowcov_to_reference.py.
  11. [Optional] Select best reference from --mapping_constrains:
  12. Mapping filtered reads to supercontig and mapping constrains(BowTie2,BWAmem2 and BWA)
  13. [Optional] Deduplicate reads (Picard or if UMI's are used UMI-tools)
  14. Variant calling and filtering (BCFTools,iVar)
  15. Create consensus genome (BCFTools,iVar)
  16. Repeat step 12-15 multiple times for the denovo contig route
  17. Consensus evaluation and annotation (QUAST,CheckV,blastn, mmseqs-search)
  18. Result summary visualisation for raw read, alignment, assembly, variant calling and consensus calling results (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
sample1,AEG588A1_S1_L002_R1_001.fastq.gz,AEG588A1_S1_L002_R2_001.fastq.gz
sample2,AEG588A5_S5_L003_R1_001.fastq.gz,
sample3,AEG588A3_S3_L002_R1_001.fastq.gz,AEG588A3_S3_L002_R2_001.fastq.gz

Each row represents a fastq file (single-end) or a pair of fastq files (paired end).

Now, you can run the pipeline using:

nextflow run nf-core/viralgenie \
   -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

Viralgenie was originally written by Joon-Klaps.

We thank the following people for their extensive assistance in the development of 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.

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.