Introduction

nf-core/nanopath pipeline is a bioinformatics tool designed for the processing of nanopore 16S/ITS sequencing data. It employs advanced clustering methods to group similar genetic sequences, facilitating the classification and reporting of bacterial and fungal constituents within input samples. The utilization of these clustering techniques contributes to a reduction in noise, minimizing the occurrence of false negatives and positives in the results. The pipeline thus serves as a reliable resource for obtaining precise insights into the microbial composition of the analyzed samples especially wihin the clinical setting.

1. Initialize the data:

   • If a fastq directory is provided:
     • Concatenate fastq files using CAT_FASTQS.

2. Validate input:

   • Use the INPUT_CHECK subworkflow to read samplesheet, validate, and stage input files.
   • Branch reads based on their status (discontinued or samples).

3. Perform Quality Control:

   • Run (FASTP) for quality control, filtering, and preprocessing.
   • Filter out samples with no reads left after FASTP.
   • Run (FASTQC) on the processed reads.

4. Classify and Cluster:

   • If specified, remove unclassified reads using (KRAKEN2).
   • Subset reads based on specified parameters (default 100k reads to keep memory requirements reasonable).
   • Perform k-mer frequency analysis with KMER_FREQS.
   • Perform read clustering with READ_CLUSTERING using (HDBSCAN) and (UMAP).

5. Split Clusters and Correct Errors:

   • Split clusters.
   • Perform error correction using (CANU).

6. Select and Polish Draft:

   • Select draft reads using (FASTANI).
   • Polish drafts using (RACON).
   • Generate final consensus using (MEDAKA).

7. Classify Taxonomically:

   • Based on chosen tool, classify consensus sequences with (BLAST), (SEQMATCH), (KRAKEN) or all of them.
   • Join classification results using JOIN_RESULTS.

8. Estimate Abundace:

   • Estimate abundance per sample per detected species.

9. Generate Reports:

   • If report generation is chosen:
     • Generate HTML reports.

Usage

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.

Now, you can run the pipeline using:

nextflow run nf-core/nanopath \
   -profile <docker/singularity/.../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, please refer to the usage documentation and the parameter documentation.

Pipeline output

To see the the results of a 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/nanopath was originally written by Magdalena Dabrowska.

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

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 #nanopath 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.

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.