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> Cantu, Vito Adrian, Jeffrey Sadural, and Robert Edwards. 2019. PRINSEQ++, a Multi-Threaded Tool for Fast and Efficient Quality Control and Preprocessing of Sequencing Datasets. e27553v1. PeerJ Preprints. doi: 10.7287/peerj.preprints.27553v1.
> Wood, Derrick E., Jennifer Lu, and Ben Langmead. 2019. Improved Metagenomic Analysis with Kraken 2. Genome Biology 20 (1): 257. doi: 10.1186/s13059-019-1891-0.
> Langmead, B., & Salzberg, S. L. (2012). Fast gapped-read alignment with Bowtie 2. Nature Methods, 9(4), 357–359. doi: 10.1038/nmeth.1923
> Breitwieser, Florian P., Daniel N. Baker, and Steven L. Salzberg. 2018. KrakenUniq: confident and fast metagenomics classification using unique k-mer counts. Genome Biology 19 (1): 198. doi: 10.1186/s13059-018-1568-0
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- [Bracken](https://doi.org/10.7717/peerj-cs.104)
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> ⚠️ This pipeline is still under development! While the pipeline is usable, not all functionality will be available!
**nf-core/taxprofiler** is a bioinformatics best-practice analysis pipeline for taxonomic classification and profiling of shotgun metagenomic data. It allows for in-parallel taxonomic identification of reads or taxonomic abundance estimation with multiple classification and profiling tools against multiple databases, produces standardised output tables.
The pipeline is built using [Nextflow](https://www.nextflow.io), 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](https://www.nextflow.io/docs/latest/dsl2.html) 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 submitted to and installed from [nf-core/modules](https://github.com/nf-core/modules) in order to make them available to all nf-core pipelines, and to everyone within the Nextflow community!
@ -24,8 +22,6 @@ The nf-core/taxprofiler CI test dataset uses sequencing data from [Maixer et al.
## Pipeline summary
<!-- TODO nf-core: Fill in short bullet-pointed list of the default steps in the pipeline -->
1. Read QC ([`FastQC`](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) or [`falco`](https://github.com/smithlabcode/falco) as an alternative option)
@ -46,7 +42,7 @@ The nf-core/taxprofiler CI test dataset uses sequencing data from [Maixer et al.
7. Present QC for raw reads ([`MultiQC`](http://multiqc.info/))
8. Plotting Kraken2, Centrifuge, Kaiju and MALT results ([`Krona`](https://hpc.nih.gov/apps/kronatools.html))
@ -98,8 +94,6 @@ For further information or help, don't hesitate to get in touch on the [Slack `#
<!-- TODO nf-core: Add citation for pipeline after first release. Uncomment lines below and update Zenodo doi and badge at the top of this file. -->
<!-- If you use nf-core/taxprofiler for your analysis, please cite it using the following doi: [10.5281/zenodo.XXXXXX](https://doi.org/10.5281/zenodo.XXXXXX) -->
<!-- TODO nf-core: Add bibliography of tools and data used in your pipeline -->
An extensive list of references for the tools used by the pipeline can be found in the [`CITATIONS.md`](CITATIONS.md) file.
You can cite the `nf-core` publication as follows:
@ -6,8 +6,6 @@ This document describes the output produced by the pipeline. Most of the plots a
The directories listed below will be created in the results directory after the pipeline has finished. All paths are relative to the top-level results directory.
<!-- TODO nf-core: Write this documentation describing your workflow's output -->
## Pipeline overview
The pipeline is built using [Nextflow](https://www.nextflow.io/) and processes data using the following steps:
James A. Fellows Yates
1 year ago
committed by