🍄🧬 MycoSNP: Whole Genome Sequencing Analysis of Fungal Isolates

Introduction

MycoSNP is a bioinformatics pipeline for performing whole genome sequencing analysis of fungal organisms (e.g. Candida auris) from Illumina paired-end reads. It is built with the nf-core template.

This repository contains two workflows that are run independently:

• Pre-MycoSNP workflow: A first-pass workflow for quick answers
  • Fungal taxonomic classification and Candida auris clade typing, using de novo assemblies
• Main MycoSNP workflow (default workflow):
  • Reference-based SNP calling
  • Tree building
  • Identification of antifungal-resistance mutations

📚 Full Documentation

• Usage: An overview of how MycoSNP works, how to run it and a description of all of the different command-line flags.
• Parameters: Options, flags, and inputs.
• Output: An overview of the different results produced by MycoSNP and how to interpret them.

Quick Start

1. Install Nextflow (>=21.10.3)

2. Install any of Docker, Singularity, Podman, Shifter or Charliecloud for full pipeline reproducibility (please only use Conda as a last resort; see docs). More info on using containers with Nextflow here.

Tip

Using Apptainer/Singularity with Nextflow version >=23 can result in failures in Linux server environments due to peculiarities with container directory mounting. If you are experiencing No such file or directory errors, try running with an earlier version of Nextflow (we've had success with 22.10.6).

3. Test the main MycoSNP workflow on pre-defined minimal test samples with a single command:

   nextflow run CDCgov/mycosnp-nf -profile test,YOURPROFILE

Note

The samples for the test run are bacterial (N. gonorrhoeae), not fungal. This is intentional so the test finishes in a few minutes (as opposed to longer for fungal samples with much larger genomes).

Tip

Note that some form of configuration will be needed so that Nextflow knows how to fetch the required software. This is usually done in the form of a config profile (YOURPROFILE in the example command above). You can chain multiple config profiles in a comma-separated string.

• The pipeline comes with config profiles called docker, singularity, podman, shifter, charliecloud and conda which instruct the pipeline to use the named tool for software management. For example, -profile test,docker.
• Please check nf-core/configs to see if a custom config file to run nf-core pipelines already exists for your Institute. If so, you can simply use -profile <institute> in your command. This will enable either docker or singularity and set the appropriate execution settings for your local compute environment.
• If you are using singularity and are persistently observing issues downloading Singularity images directly due to timeout or network issues, then you can use the --singularity_pull_docker_container parameter to pull and convert the Docker image instead. Alternatively, you can use the nf-core download command to download images first, before running the pipeline. Setting the NXF_SINGULARITY_CACHEDIR or singularity.cacheDir Nextflow options enables you to store and re-use the images from a central location for future pipeline runs.
• If you are using conda (not recommended), it is highly recommended to use the NXF_CONDA_CACHEDIR or conda.cacheDir settings to store the environments in a central location for future pipeline runs.

4. Start running your own analysis!

Note

The --workflow option specifies which workflow to run (Pre-MycoSNP workflow or main MycoSNP workflow). By default (when no workflow is specified), the main MycoSNP workflow is executed. See summaries of each workflow in the next section, or more detailed documentation in the Full Documentation.

• Pre-MycoSNP workflow:

  nextflow run CDCgov/mycosnp-nf --workflow PRE_MYCOSNP -profile <docker/singularity/other/institute> --input samplesheet.csv

• Main MycoSNP workflow (default workflow):

  nextflow run CDCgov/mycosnp-nf -profile <docker/singularity/other/institute> --input samplesheet.csv --fasta reference_genome.fasta

5. It is advisable to delete large temporary or log files after the successful completion of the run. It takes a lot of space and may cause issues in future runs.

Pre-MycoSNP Workflow: Summary

1. Sequencing reads quality metrics (FastQC)
2. Remove unpaired reads (seqkit pair)​
3. Trim/filter reads (FaQCs)​
4. De novo assembly (Shovill)
   • Downsampling​ (default 70X)
   • Assembly (with SKESA [default], SPAdes, Megahit, or Velvet​)
5. Taxonomic classification (GAMBIT)
   • Classifies isolate to genus/species level, if possible
   • Uses GAMBIT's fungal database v0.2.0. See GAMBIT'S documentation for a list of taxa included in the database.
6. Subtyping (sourmash)
   • Compares sourmash sketch of sample against sourmash signature file provided in assets/sourmash_db/.
   • By default, for C. auris, Pre-MycoSNP performs clade typing (Clades I-VI).
7. Summary report containing genus/species classification, subtype, and read and assembly quality metrics.

Main MycoSNP Workflow (Default Workflow): Summary

Reference Preparation

Prepares a reference FASTA file for BWA alignment and GATK variant calling by masking repeats in the reference and generating the BWA index.

• Genome repeat identification and masking (nucmer)
• BWA index generation (bwa)
• FAI and DICT file creation (Picard, Samtools)

Sample QC and Processing

Prepares samples (paired-end FASTQ files) for GATK variant calling by aligning the samples to a BWA reference index and ensuring that the BAM files are correctly formatted. This step also provides different quality reports for sample evaluation.

• Combine FASTQ file lanes if they were provided with multiple lanes.
• Filter unpaired reads from FASTQ files (SeqKit).
• Down sample FASTQ files to a desired coverage or sampling rate (SeqTK).
• Trim reads and assess quality (FaQCs).
• Generate a QC report by extracting data from FaQCs report data.
• Align FASTQ reads to a reference (BWA).
• Sort BAM files (SAMTools).
• Mark and remove duplicates in the BAM file (Picard).
• Clean the BAM file (Picard "CleanSam").
• Fix mate information in the BAM file (Picard "FixMateInformation").
• Add read groups to the BAM file (Picard "AddOrReplaceReadGroups").
• Index the BAM file (SAMTools).
• FastQC - Filtered reads QC.
• Qualimap mapping quality report.
• MultiQC - Aggregate report describing results and QC from the whole pipeline

Variant calling and analysis

Calls variants and generates a multi-FASTA file and phylogeny.

• Call variants (GATK HaplotypeCaller).
• Combine gVCF files from the HaplotypeCaller into a single VCF (GATK CombineGVCFs).
• Call genotypes using the (GATK GenotypeGVCFs).
• Filter the variants (GATK VariantFiltration) [default (but customizable) filter: 'QD < 2.0 || FS > 60.0 || MQ < 40.0 || DP < 10'].
• Run a customized VCF filtering script (Broad Institute).
• Split the filtered VCF file by sample.
• Select only SNPs from the VCF files (GATK SelectVariants).
• Split the VCF file with SNPs by sample.
• Create a multi-fasta file from the VCF SNP positions using a custom script (Broad Institute).
• Create a distance matrix file using multi-fasta file(SNPdists).
• Create phylogeny from multi-fasta file (rapidNJ, FastTree2, quicksnp, RaxML(optional), IQTree(optional))

Variant annotation analysis (currently available for C. auris B11205 genome only)

• annotated VCF file (snpEff)
• snpeffr report. Non-synonymous variants in FKS1 hotspot regions are included in the report.

Pre-configured Nextflow development environment using Gitpod

Once the pod launches, it will present a VS-Code interface and comes with Nextflow, Conda and Docker pre-installed

Credits

nf-core/mycosnp was originally developed at CDC (with contributions from many others in the public health bioinformatics community), and is currently maintained by CDC's Mycotic Diseases Branch.

We thank the following people (alphabetical order by last name) for their code contributions or assistance in the development of this pipeline:

• John Arnn @jwarnn
• Ujwal Bagal @urbagal
• Arun Boddapati @arunbodd
• Michael Cipriano @mjcipriano
• Lynn Dotrang @leuthrasp
• Jared Johnson @DOH-JDJ0303
• Christopher Jossart @cjjossart
• Elizabeth Misas @AspTryGlu
• Drewry Morris @drewry
• Zack Mudge @zmudge3
• Harshil Patel @drpatelh
• Sateesh Peri @sateeshperi
• Robert A. Petit III @rpetit3
• Malavika Rajeev @mrajeev08
• Charlotte Royer @royercj
• Chris Sandlin @cssandlin
• Hunter Seabolt @hseabolt

Special thanks to StaPH-B for open-source collaborations and discussions.

Special thanks to CDC's Office of Advanced Molecular Detection (OAMD) and the Scientific Computing and Bioinformatics Support (SciComp) team for supporting development and computing infrastructure.

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 MycoSNP and nf-core publications as follows:

Bagal UR, Phan J, Welsh RM, Misas E, Wagner D, Gade L, Litvintseva AP, Cuomo CA, Chow NA.

MycoSNP: A Portable Workflow for Performing Whole-Genome Sequencing Analysis of Candida auris.

Methods Mol Biol. 2022; 2517:215-228. doi: 10.1007/978-1-0716-2417-3_17

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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