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      "description": "<h1>\n  <picture>\n    <source media=\"(prefers-color-scheme: dark)\" srcset=\"docs/images/nf-core-metatdenovo_logo_dark.png\">\n    <img alt=\"nf-core/metatdenovo\" src=\"docs/images/nf-core-metatdenovo_logo_light.png\">\n  </picture>\n</h1>\n\n[![GitHub Actions CI Status](https://github.com/nf-core/metatdenovo/actions/workflows/nf-test.yml/badge.svg)](https://github.com/nf-core/metatdenovo/actions/workflows/nf-test.yml)\n[![GitHub Actions Linting Status](https://github.com/nf-core/metatdenovo/actions/workflows/linting.yml/badge.svg)](https://github.com/nf-core/metatdenovo/actions/workflows/linting.yml)[![AWS CI](https://img.shields.io/badge/CI%20tests-full%20size-FF9900?labelColor=000000&logo=Amazon%20AWS)](https://nf-co.re/metatdenovo/results)[![Cite with Zenodo](http://img.shields.io/badge/DOI-10.5281/zenodo.10666590-1073c8?labelColor=000000)](https://doi.org/10.5281/zenodo.10666590)\n[![nf-test](https://img.shields.io/badge/unit_tests-nf--test-337ab7.svg)](https://www.nf-test.com)\n\n[![Nextflow](https://img.shields.io/badge/version-%E2%89%A524.10.5-green?style=flat&logo=nextflow&logoColor=white&color=%230DC09D&link=https%3A%2F%2Fnextflow.io)](https://www.nextflow.io/)\n[![nf-core template version](https://img.shields.io/badge/nf--core_template-3.3.2-green?style=flat&logo=nfcore&logoColor=white&color=%2324B064&link=https%3A%2F%2Fnf-co.re)](https://github.com/nf-core/tools/releases/tag/3.3.2)\n[![run with conda](http://img.shields.io/badge/run%20with-conda-3EB049?labelColor=000000&logo=anaconda)](https://docs.conda.io/en/latest/)\n[![run with docker](https://img.shields.io/badge/run%20with-docker-0db7ed?labelColor=000000&logo=docker)](https://www.docker.com/)\n[![run with singularity](https://img.shields.io/badge/run%20with-singularity-1d355c.svg?labelColor=000000)](https://sylabs.io/docs/)\n[![Launch on Seqera Platform](https://img.shields.io/badge/Launch%20%F0%9F%9A%80-Seqera%20Platform-%234256e7)](https://cloud.seqera.io/launch?pipeline=https://github.com/nf-core/metatdenovo)\n\n[![Get help on Slack](http://img.shields.io/badge/slack-nf--core%20%23metatdenovo-4A154B?labelColor=000000&logo=slack)](https://nfcore.slack.com/channels/metatdenovo)[![Follow on Bluesky](https://img.shields.io/badge/bluesky-%40nf__core-1185fe?labelColor=000000&logo=bluesky)](https://bsky.app/profile/nf-co.re)[![Follow on Mastodon](https://img.shields.io/badge/mastodon-nf__core-6364ff?labelColor=FFFFFF&logo=mastodon)](https://mstdn.science/@nf_core)[![Watch on YouTube](http://img.shields.io/badge/youtube-nf--core-FF0000?labelColor=000000&logo=youtube)](https://www.youtube.com/c/nf-core)\n\n## Introduction\n\n**nf-core/metatdenovo** is a bioinformatics best-practice analysis pipeline for assembly and annotation of metatranscriptomic and metagenomic data from prokaryotes, eukaryotes or viruses.\n\nOn release, automated continuous integration tests run the pipeline on a full-sized dataset on the AWS cloud infrastructure. This ensures that the pipeline runs on AWS, has sensible resource allocation defaults set to run on real-world datasets, and permits the persistent storage of results to benchmark between pipeline releases and other analysis sources. The results obtained from the full-sized test can be viewed on the [nf-core website](https://nf-co.re/metatdenovo/results).\n\n## Usage\n\n![nf-core/metatdenovo metro map](docs/images/metat-metromap.png)\n\n1. Read QC ([`FastQC`](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/))\n2. Present QC for raw reads ([`MultiQC`](http://multiqc.info/))\n3. Quality trimming and adapter removal for raw reads ([`Trim Galore!`](https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/))\n4. Optional: Filter sequences with [`BBduk`](https://jgi.doe.gov/data-and-tools/software-tools/bbtools/bb-tools-user-guide/bbduk-guide/)\n5. Optional: Normalize the sequencing depth with [`BBnorm`](https://jgi.doe.gov/data-and-tools/software-tools/bbtools/bb-tools-user-guide/bbnorm-guide/)\n6. Merge trimmed, pair-end reads ([`Seqtk`](https://github.com/lh3/seqtk))\n7. Choice of de novo assembly programs:\n   1. [`RNAspades`](https://cab.spbu.ru/software/rnaspades/) suggested for both prokaryote and eukaryote assembly\n   2. [`Megahit`](https://github.com/voutcn/megahit) suggested for both prokaryote and eukaryote assembly; requires less resources\n8. Choice of orf caller:\n   1. [`TransDecoder`](https://github.com/TransDecoder/TransDecoder) suggested for eukaryotes; only ORFs\n   2. [`Prokka`](https://github.com/tseemann/prokka) suggested for prokaryotes; ORFs and other features plus functional annotation\n   3. [`Prodigal`](https://github.com/hyattpd/Prodigal) suggested for Prokaryotes; only ORFs\n9. Quantification of genes identified in assemblies:\n   1. Generate index of assembly ([`BBmap index`](https://sourceforge.net/projects/bbmap/))\n   2. Mapping cleaned reads to the assembly for quantification ([`BBmap`](https://sourceforge.net/projects/bbmap/))\n   3. Get raw counts per each gene present in the assembly ([`Featurecounts`](http://subread.sourceforge.net)) -> TSV table with collected featurecounts output\n10. Functional annotation:\n    1. [`Prokka`](https://github.com/tseemann/prokka) feature identification and annotation for prokaryotes\n    2. [`eggNOG-mapper`](https://github.com/eggnogdb/eggnog-mapper)\n    3. [`KofamScan`](https://github.com/takaram/kofam_scan)\n    4. [`HMMER`](https://www.ebi.ac.uk/Tools/hmmer/search/hmmsearch) search ORFs with a set of HMM profiles, and rank results\n11. Taxonomic annotation:\n    1. [`EUKulele`](https://github.com/AlexanderLabWHOI/EUKulele)\n    2. [`Diamond`](https://github.com/bbuchfink/diamond)\n12. Summary statistics.\n\n## Usage\n\n> [!NOTE]\n> If you are new to Nextflow and nf-core, please refer to [this page](https://nf-co.re/docs/usage/installation) on how to set-up Nextflow. Make sure to [test your setup](https://nf-co.re/docs/usage/introduction#how-to-run-a-pipeline) with `-profile test` before running the workflow on actual data.\n\nFirst, prepare a samplesheet with your input data that looks as follows:\n\n`samplesheet.csv`:\n\n```\nsample,fastq_1,fastq_2\nsample1,./data/S1_R1_001.fastq.gz,./data/S1_R2_001.fastq.gz\nsample2,./data/S2_fw.fastq.gz,./data/S2_rv.fastq.gz\nsample3,./S4x.fastq.gz,./S4y.fastq.gz\nsample3,./a.fastq.gz,./b.fastq.gz\n```\n\nEach row represents a fastq file (single-end) or a pair of fastq files (paired-end).\nThe fastq files need to end with `.fq` or `.fastq`, followed by `.gz` if gzipped.\nRead files from multiple rows with the same sample name will be concatenated and treated as a single sample.\nA mix of single-end and paired-end files is allowed, but do not mix single-end and paired-end for the same sample name.\n\nNow, you can run the pipeline using:\n\n```bash\nnextflow run nf-core/metatdenovo \\\n   -profile <docker/singularity/.../institute> \\\n   --input samplesheet.csv \\\n   --outdir <OUTDIR>\n```\n\n> [!WARNING]\n> 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](https://nf-co.re/docs/usage/getting_started/configuration#custom-configuration-files).\n\nFor more details and further functionality, please refer to the [usage documentation](https://nf-co.re/metatdenovo/usage) and the [parameter documentation](https://nf-co.re/metatdenovo/parameters).\n\n## Pipeline output\n\nTo see the results of an example test run with a full size dataset refer to the [results](https://nf-co.re/metatdenovo/results) tab on the nf-core website pipeline page.\nFor more details about the output files and reports, please refer to the\n[output documentation](https://nf-co.re/metatdenovo/output).\n\n> [!NOTE]\n> Tables in the `summary_tables` directory under the output directory are made especially for further analysis in tools like R or Python.\n> Their formats are standardized and column names consistent between tables.\n\n## Credits\n\nnf-core/metatdenovo was originally written by Danilo Di Leo (@danilodileo), Emelie Nilsson (@emnilsson) & Daniel Lundin (@erikrikarddaniel).\n\n## Contributions and Support\n\nIf you would like to contribute to this pipeline, please see the [contributing guidelines](.github/CONTRIBUTING.md).\n\nFor further information or help, don't hesitate to get in touch on the [Slack `#metatdenovo` channel](https://nfcore.slack.com/channels/metatdenovo) (you can join with [this invite](https://nf-co.re/join/slack)).\n\n## Citations\n\nIf you use nf-core/metatdenovo for your analysis, please cite it using the following doi: [10.5281/zenodo.10666590](https://doi.org/10.5281/zenodo.10666590)\n\nAn extensive list of references for the tools used by the pipeline can be found in the [`CITATIONS.md`](CITATIONS.md) file.\n\nYou can cite the `nf-core` publication as follows:\n\n> **The nf-core framework for community-curated bioinformatics pipelines.**\n>\n> Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.\n>\n> _Nat Biotechnol._ 2020 Feb 13. doi: [10.1038/s41587-020-0439-x](https://dx.doi.org/10.1038/s41587-020-0439-x).\n",
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