Introduction

nf-uno is a bioinformatics pipeline for the co-assembly, binning, and read mapping of mNGS outbreak samples from the The UnO project

Pipeline summary

UnO is an mNGS bioinformatics pipeline that supports The UnO Project. nf-core UnO is the second tier The UnO project which analyzes set of mNGS reads from a well-characterized outbreak. The draft UnO pipeline takes as input outbreak sets of mNGS reads. Reads are co-assembled into a single outbreak assembly and then binned into Metagenomic Assembled Genomes (MAGs). Individual mNGS reads are mapped back to MAGs to identify individual sample contributions. MAGs in common across individual mNGS reads are chosen for further analysis and characterization.
<!-- TODO nf-core: Include a figure that guides the user through the major workflow steps. Many nf-core workflows use the "tube map" design for that. See https://nf-co.re/docs/contributing/design_guidelines#examples for examples. --> <!-- TODO nf-core: Fill in short bullet-pointed list of the default steps in the pipeline -->

1. Inital reference-based taxonomic classfication of reads is performed using (MIDAS2)
2. Read QC (FastQC)
3. Perform quality and adapter trimming on raw reads (Trimmomatic)
4. Read QC on trimmed reads
5. Co-assemble mNGS reads from outbreak dataset into single outbreak assembly (Megahit)
6. Preparation for binning of metagenomic co-assembly with (Bowtie2). Outbreak co-assembly is used to create an index which individual reads are mapped to determine depth information for downstream binning tools.
7. (MetaBat2) and (MaxBin2) are used to bin MAGs.
8. (DAStool) is optionally used to refine bins.
9. (Bowtie2) is used to map individual reads back to bins to identify MAGs in common across outbreak samples.
10. (CheckM) is used to asses quality of bins.
11. (GTDB-tk) is used to assign taxonomy to bins.
12. (MultiQC) is used to summarize some of the findings and software versions.

Workflow

Usage

Running nf-uno requires Nextflow (>=21.10.3) and conda to be installed. There are detailed instructions below for Nextflow installation, including Nextflow's Bash and Java requirements. Conda is required for the MIDAS2 process therefore, we recommend using conda for all required dependencies.

[!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. For conda installation, please refer to this page.

When Nextflow and conda are installed, clone the pipeline: console git clone https://github.com/uel3/nf-uno

Next, run a minimal on the minimal dataset provided using the test.config:

console nextflow run nf-uno -profile conda,test --outdir <OUTDIR> To run a full test of all tools in the pipeline with the minimal dataset, use the test_full.config:

console nextflow run nf-uno -profile conda,test_full --outdir <OUTDIR>

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

samplesheet.csv:

csv sample,group,short_reads_1,short_reads_2, SAMPLE1,UnO,/path/to/reads/SAMPLE1_1.fastq.gz,/path/to/reads/SAMPLE1_2.fastq.gz, SAMPLE2,UnO,/path/to/reads/SAMPLE2_1.fastq.gz,/path/to/reads/SAMPLE2_2.fastq.gz, SAMPLE3,UnO,/path/to/reads/SAMPLE3_1.fastq.gz,/path/to/reads/SAMPLE3_2.fastq.gz,

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

Now, you can run the pipeline using:

bash nextflow run nf-uno \ -profile <conda/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. For an example analysis with output please refer to the example usage

Pipeline output

Current output of the draft UnO output consists of the user specified with following directories: Assembly, FastQC, GenomeBinning, MIDAS2, multiqc, pipelineinfo, QCshortreads, Taxonomy, and Trimmomatic. For more details about the output files and reports, please refer to the output documentation.

Credits

uel3/nf-uno is adapted by Candace Cole from nf-core/mag, written by Hadrien Gourlé at SLU, Daniel Straub and Sabrina Krakau at the Quantitative Biology Center (QBiC).

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

Andrew Huang

Rong Jin

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.

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