nf-core/viralmetagenome

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Introduction

Viralmetagenome 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.

1. Read QC (FastQC)
2. Performs optional read pre-processing
   • Adapter trimming(fastp, Trimmomatic)
   • Read UMI deduplication (HUMID)
   • [Optional] Combining of reads (CAT)
   • Low complexity and quality filtering (bbduk, prinseq++)
   • Host-read removal (BowTie2)
3. Metagenomic diversity mapping
   • Performs taxonomic classification and/or profiling using one or more of:
     • Kraken2
     • Bracken(optional)
     • Kaiju
   • 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. [Optional] Map reads to contigs for coverage estimation (BowTie2,BWAmem2 and BWA)
7. Contig reference idententification (blastn)
   • Identify top 5 blast hits
   • Merge blast hit and all contigs of a sample
8. [Optional] Precluster contigs based on taxonomy
   • Identify taxonomy Kraken2 and\or Kaiju
   • Resolve potential inconsistencies in taxonomy & taxon filtering | simplification bin/extract_precluster.py
9. Cluster contigs (or every taxonomic bin) of samples, options are:
   • cdhitest
   • vsearch
   • mmseqs-linclust
   • mmseqs-cluster
   • vRhyme
   • Mash
10. [Optional] Remove clusters with low read coverage. bin/extract_clusters.py
11. Scaffolding of contigs to centroid (Minimap2, iVar-consensus)
12. [Optional] Annotate 0-depth regions with external reference bin/nocov_to_reference.py.
13. [Optional] Select best reference from --mapping_constraints:
    • Mash sketch
    • Mash screen
14. Mapping filtered reads to supercontig and mapping constraints(BowTie2,BWAmem2 and BWA)
15. [Optional] Deduplicate reads (Picard or if UMI’s are used UMI-tools)
16. Variant calling and filtering (BCFTools,iVar)
17. Create consensus genome (BCFTools,iVar)
18. Repeat step 14-17 multiple times for the denovo contig route
19. [Optional] Variant annotation (SnpEff,SnpSift)
20. [Optional] Consensus evaluation and annotation:
    • QUAST
    • CheckV
    • blastn
    • prokka
    • mmseqs-search
    • MAFFT - alignment of contigs vs iterations & consensus
21. Result summary visualisation for raw read, alignment, assembly, variant calling and consensus calling results (MultiQC)

Usage

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/viralmetagenome \
   -profile <docker/singularity/.../institute> \
   --input samplesheet.csv \
   --outdir <OUTDIR>

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/viralmetagenome was originally written by Joon Klaps, Philippe Lemey, Liana Kafetzopoulou.

We thank the following people for their extensive assistance in the development of this pipeline:

• Philippe Lemey
• Liana Kafetzopoulou
• nf-core community

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 #viralmetagenome channel (you can join with this invite).

Citations

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

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. —>