Introduction

ncezid-biome/stylo is a bioinformatics pipeline that can be used to filter, downsample, assemble, and QC ONT longreads. It takes a samplesheet and FASTQ files as input, performs read filtering, downsampling to specified coverage, assembly, and Quality Control (QC).

1. Filters low quality reads (nanoq)
2. Downsamples reads to specific coverage (rasusa)
3. Assembles reads (Flye)
4. Reorients assembly (Dnaapler)
5. Error correction (Medaka)
6. QCs assembly (busco)

Usage

[!NOTE] If you are new to Nextflow and nf-core, please refer to this page on how to set-up Nextflow.

[!NOTE] This pipeline was tested using the following, other versions may work but are currently untested

nf-core v2.14.1

nextflow v24.04.2

singularity v3.8.7

First, download this branch to your preferred directory bash cd /path/to/dir/ git clone -b nf-core-dev git@github.com:ncezid-biome/stylo.git

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

samplesheet.csv:

csv sample,fastq,genus,species sample1,/path/to/sample1.fastq.gz,Salmonella,enterica sample2,/path/to/sample2.fastq.gz,Campylobacter,coli sample3,/path/to/sample3.fastq.gz,Campylobacter,jejuni sample4,/path/to/sample4.fastq.gz,Vibrio,- sample5,/path/to/sample5.fastq.gz,Salmonella,enterica

Each row represents a fastq file (single-end) with the known genus and species.

[!NOTE] you can use - where the species is unknown

Third, look at the lookup table to make sure that each genus listed in your samplesheet is present. If you'd like to add a row or edit the lookup table see Advanced Usage

Now, you can run the pipeline using:

bash nextflow run /path/to/stylo/main.nf \ -profile singularity --input samplesheet.csv \ --outdir <OUTDIR>

If you're on CDC servers use -profile rosalind

[!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 about generic usage see the Usage Page

Advanced Usage

Editing the Lookup Table

If a genus is missing, then you'll need to add a row to the lookup table prior to running the pipeline. In order to add a row to the lookup table you'll need the following information:

1. genus (required)
2. species (optional, use - if you want the lookup table to accept all species within that genus)
3. genomes size (required, must follow the same format as the other rows in MBs)

model parameter

If the model parameter is left blank, the pipeline will choose the bacterial methylation model r1041_e82_400bps_bacterial_methylation. It's best to let the pipleine use the bacterial methylation model, but if you must specify the model parameter make sure to use one of the models from the following list

r103_sup_g507 r1041_e82_260bps_fast_g632 r1041_e82_260bps_hac_g632 r1041_e82_260bps_hac_v4.0.0 r1041_e82_260bps_hac_v4.1.0 r1041_e82_260bps_joint_apk_ulk_v5.0.0 r1041_e82_260bps_sup_g632 r1041_e82_260bps_sup_v4.0.0 r1041_e82_260bps_sup_v4.1.0 r1041_e82_400bps_bacterial_methylation r1041_e82_400bps_fast_g615 r1041_e82_400bps_fast_g632 r1041_e82_400bps_hac_g615 r1041_e82_400bps_hac_g632 r1041_e82_400bps_hac_v4.0.0 r1041_e82_400bps_hac_v4.1.0 r1041_e82_400bps_hac_v4.2.0 r1041_e82_400bps_hac_v4.3.0 r1041_e82_400bps_hac_v5.0.0 r1041_e82_400bps_hac_v5.0.0_rl_lstm384_dwells r1041_e82_400bps_hac_v5.0.0_rl_lstm384_no_dwells r1041_e82_400bps_hac_v5.2.0 r1041_e82_400bps_hac_v5.2.0_rl_lstm384_dwells r1041_e82_400bps_hac_v5.2.0_rl_lstm384_no_dwells r1041_e82_400bps_sup_g615 r1041_e82_400bps_sup_v4.0.0 r1041_e82_400bps_sup_v4.1.0 r1041_e82_400bps_sup_v4.2.0 r1041_e82_400bps_sup_v4.3.0 r1041_e82_400bps_sup_v5.0.0 r1041_e82_400bps_sup_v5.0.0_rl_lstm384_dwells r1041_e82_400bps_sup_v5.0.0_rl_lstm384_no_dwells r1041_e82_400bps_sup_v5.2.0 r1041_e82_400bps_sup_v5.2.0_rl_lstm384_dwells r1041_e82_400bps_sup_v5.2.0_rl_lstm384_no_dwells r104_e81_fast_g5015 r104_e81_hac_g5015 r104_e81_sup_g5015 r104_e81_sup_g610 r941_e81_fast_g514 r941_e81_hac_g514 r941_e81_sup_g514 r941_min_fast_g507 r941_min_hac_g507 r941_min_sup_g507 r941_prom_fast_g507 r941_prom_hac_g507 r941_prom_sup_g507

for more details about model selection in medaka, see medaka model documentation

Credits

ncezid-biome/stylo was originally written by Arzoo Patel, Mohit Thakur.

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

Justin Kim, Jessica Chen, Peyton Smith, Lee S. Katz, Joe Wirth, Curtis Kapsak

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.

This pipeline uses code and infrastructure developed and maintained by the nf-core community, reused here under the MIT license.

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.