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» nextflow run nf-core/bacass -r 1.1.0 -profile test
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Introduction

Short Read Assembly

This pipeline is primarily for bacterial assembly of next-generation sequencing reads. It can be used to quality trim your reads using Skewer and performs basic sequencing QC using FastQC. Afterwards, the pipeline performs read assembly using Unicycler. Contamination of the assembly is checked using Kraken2 to verify sample purity.

Long Read Assembly

For users that only have Nanopore data, the pipeline quality trims these using PoreChop and assesses basic sequencing QC utilizing NanoPlot and PycoQC. The pipeline can then perform long read assembly utilizing Unicycler, Miniasm in combination with Racon or Canu. Long reads can be polished using specified Fast5 files with NanoPolish.

Hybrid Assembly

For users specifying both short read and long read (NanoPore) data, the pipeline can perform a hybrid assembly approach utilizing Unicycler, taking the full set of information from short reads and long reads into account.

Shared QC across all forms of assembly

In all cases, the assembly is assessed using QUAST. The resulting bacterial assembly is furthermore annotated using Prokka.

In addition, the pipeline creates various reports in the results directory specified, including a MultiQC report summarizing some of the findings and software versions.

The pipeline is built using Nextflow, a workflow tool to run tasks across multiple computing infrastructures in a portable manner. It comes with docker or singularity containers as well as conda environments, making installation trivial and results highly reproducible.

Documentation

The nf-core/bacass pipeline comes with documentation about the pipeline, found in the docs/ directory:

  1. Installation
  2. Pipeline configuration
  3. Running the pipeline
  4. Output and how to interpret the results
  5. Troubleshooting

Credits

nf-core/bacass was originally written by Andreas Wilm and is currently maintained by Alexander Peltzer.

Citation

If you use nf-core/atacseq for your analysis, please cite it using the following doi: 10.5281/zenodo.2634132

You can cite the nf-core pre-print as follows:
Ewels PA, Peltzer A, Fillinger S, Alneberg JA, Patel H, Wilm A, Garcia MU, Di Tommaso P, Nahnsen S. nf-core: Community curated bioinformatics pipelines. bioRxiv. 2019. p. 610741. doi: 10.1101/610741.