CDC Pertussis and Diphtheria Laboratory

Culture-Independent Whole Genome Sequencing (CIWGS) Read Filter Pipeline 🧪🧬🖥️

Introduction

bpertussisciwgs is a bioinformatics best-practice analysis pipeline for processing Illumina reads prepared through Culture-Independent WGS of B. pertussis positive clinical specimens.

The pipeline is built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It uses Docker/Singularity containers making installation trivial and results highly reproducible. The Nextflow DSL2 implementation of this pipeline uses one container per process which makes it much easier to maintain and update software dependencies. Where possible, these processes have been installed from nf-core/modules in order to make them available to all nf-core pipelines, and to everyone within the Nextflow community! Some documentation has been automatically generated by nf-core and may not be accurate.

Pipeline summary

1. Raw read QC (FastQC)
2. Subtractive read mapping to a human reference assembly (bowtie2)
3. Positive read mapping to a B. pertussis reference assembly (bowtie2+samtools)
4. Optional: De novo assembly of filtered reads (skesa+QUAST)
5. Optional: MLST/cgMLST/wgMLST typing gene coverage calculations (samtools)
6. Compute read recovery and coverage metrics (custom)
7. Present QC for raw reads (MultiQC)

Quick start

1. Install Nextflow (>=21.04.0)

   CDC Users: On CDC SciComp infrastructure use:
   console module load nextflow

2. Install any of Docker, Singularity, Podman, Shifter or Charliecloud for full pipeline reproducibility (please only use Conda as a last resort; see docs)

   CDC Users: Only singularity containers should be used on CDC SciComp infrastructure (biolinux, aspen, rosalind).

3. Clone the pipeline repo to your working environment:

   console git clone git@github.com:CDCgov/bpertussis-ciwgs.git

4. Test the pipeline using a minimal dataset using the command:

   console nextflow run Bpertussis-CIWGS/main.nf -profile test,singularity

5. Start running your own analysis!

   Prepare a sample sheet for use as the pipeline input, which should consist of three comma-separated columns with: sample-ID, path(Read1.fastq), path(Read2.fastq). For single-end read data, only one FASTQ should be speficied. Example: console sample,fastq_1,fastq_2 CONTROL_REP1,AEG588A1_S1_L002_R1_001.fastq.gz,AEG588A1_S1_L002_R2_001.fastq.gz Run the pipeline: console nextflow run Bpertussis-CIWGS/main.nf -profile sge,singularity --input {SAMPLESHEET.csv} --outdir {OUTDIR} --fasta {BPERTUSSIS.fasta} --hsref {PATH/TO/humanref/bowtie-index} --mlst {TYPING-GENES.fasta} --skesa true|false

Documentation

The bpertussisciwgs pipeline comes with documentation about general
- usage
- output
- training

Workflow diagram

Running on CDC HPC

For use on an HPC cluster (rosalind, aspen) the workflow can be run as a job by the following steps:

1) After logging in, activate the nextflow environment:

```console
module load nextflow
```

2) Prepare file cdc.confing with the necessary sge submission parameters, add it to your ./conf/, and include it in nextflow.config with:

```groovy
// Load CDC config for operating on internal compute infrastructure
includeConfig 'conf/cdc.config'
```

3) Submit individual processes as jobs to the scheduler using a profile defined in cdc.config, for example:

```consol
-profile sge,singularity
-profile sgeaspen,singularity
```

Credits

The bpertussisciwgs workflow was originally written by Michael R. Weigand.

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 CITATIONS.md.

Please cite:

Strengthening Bordetella pertussis genomic surveillance by direct sequencing of residual positive specimens.

Yanhui Peng, Margaret M. Williams, Lingzi Xiaoli, Ashley Simon, Heather Fueston, M. Lucia Tondella, & Michael R. Weigand

bioRxiv. 2023. doi: 10.1101/2023.12.08.570824

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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