nf-core/genomeqc

nf-core/genomeqc

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The pipeline takes a list of genomes and annotations (from local files or ncbi accessions), and runs commonly used tools to assess their quality. Depending on the inputs provided, there are two ways this pipeline can run: 1. Genome only (minmal run, only fasta files are supplied) 2. Genome and Annotation (both fasta and gtf/gff files are supplied) nf-core/genomeqc **1. Genome Only:** 1. Downloads the genome files from NCBI: [NCBI genome download](https://github.com/kblin/ncbi-genome-download) - Or **provide your own genomes**. 2. Describes genome assembly: 1. [BUSCO](https://busco.ezlab.org/): Evaluates genome completeness based on **single copy markers**. 2. **BUSCO Ideogram**: Plots the location of BUSCO markers in the assembly. 3. [tidk](https://github.com/tolkit/telomeric-identifier) (optional): Identifies and visualises telomeric repeats. 4. [QUAST](https://github.com/ablab/quast): Computes contiguity and integrity statistics such as N50, N90, GC%, and the number of sequences. 5. Contamination screening: - [FCS-GX](https://github.com/ncbi/fcs/wiki/FCS-GX-quickstart): Detection and removal of foreign organism contamination. - [FCS-adaptor](https://github.com/ncbi/fcs/wiki/FCS-adaptor-quickstart): Detection and removal of adaptor and vector contamination. - [Tiara](https://ibe-uw.github.io/tiara/): DNA sequence classification. 3. Plots a BUSCO marker-based phylogenetic tree with assembly summary statistics: **Tree Summary**. 4. Summary with [MultiQC](http://multiqc.info). **2. Genome and Annotation:** 1. Downloads the genome and gene annotation files from NCBI: [NCBI genome download](https://github.com/kblin/ncbi-genome-download) - Or **provide your own genomes and annotations**. 2. Describes genome assembly: 1. [BUSCO](https://busco.ezlab.org/): Evaluates genome completeness based on **single copy markers**. 2. **BUSCO Ideogram**: Plots the location of markers on the assembly. 3. [Merqury](https://github.com/marbl/merqury) (optional): Evaluates genome completeness based on sequencing reads. 4. [tidk](https://github.com/tolkit/telomeric-identifier) (optional): Identifies and visualises telomeric repeats. 5. [QUAST](https://github.com/ablab/quast): Computes contiguity and integrity statistics: N50, N90, GC%, number of sequences. 6. Contamination screening: - [FCS-GX](https://github.com/ncbi/fcs/wiki/FCS-GX-quickstart): Detection and removal of foreign organisms contamination. - [FCS-adaptor](https://github.com/ncbi/fcs/wiki/FCS-adaptor-quickstart): Detection and removal of adaptor and vector contamination. - [Tiara](https://ibe-uw.github.io/tiara/): DNA sequence classification. 7. More options... 3. Describes annotation : 1. [AGAT](https://agat.readthedocs.io/en/latest/): Number of genes, features, length... 2. **Gene Overlaps**: Finds the number of overlapping genes. 4. Extracts longest protein isoform: [GffRead](https://github.com/gpertea/gffread). 5. Finds orthologous genes: [Orthofinder](https://github.com/davidemms/OrthoFinder). 6. Plots an orthology-based phylogenetic tree with assembly and annotation summary statistics: **Tree Summary**. 7. Summary with [MultiQC](http://multiqc.info). The pipeline outputs an executable that launches a shiny app with the tree plot and the summary statistics. The plot's parameters can be modified, and summary statistics can be added or removed in real time. Once the plot has been adjusted, it can be saved as png/svg. > [!WARNING] > We strongly suggest users to specify the lineage using the `--busco_lineage` parameter, as setting the lineage to `auto` (default value) might cause problems with `BUSCO` during the lineage determination step. > [!NOTE] > `BUSCO Ideogram` will only plot those chromosomes -or scaffolds- that contain at least one single copy marker. ## Usage > [!NOTE] > If you are new to Nextflow and nf-core, please refer to [this page](https://nf-co.re/docs/get_started/environment_setup/overview) on how to set-up Nextflow. Make sure to [test your setup](https://nf-co.re/docs/get_started/run-your-first-pipeline) with `-profile test` before running the workflow on actual data. First, prepare an input **samplesheet** in **csv format** (e.g. `samplesheet.csv`). You can prepare your sampplesheet using: ### 1. Local files Simply point out to your local genome assembly and annotation (in FASTA and GFF format, respectively) using the `fasta` and `gff` fields: ```csv species,fasta,gff species_1,/path/to/genome1.fasta,/path/to/annotation1.gff3 species_2,/path/to/genome2.fasta,/path/to/annotation2.gff3 species_3,/path/to/genome3.fasta,/path/to/annotation3.gff3 ``` ### 2. ncbi accessions Additionally, you can run the pipeline providing ncbi accessions (RefSeq or GenBank, depeding on the mode you wish to run) in the `ncbi` field: ```csv species,ncbi species_1,GCF_000000001.1 species_2,GCF_000000002.1 species_3,GCF_000000003.1 ``` ### 3. Both You can combine both input types in the same samplesheet: ```csv species,ncbi,fasta,gff species_1,GCF_000000001.1 species_2,,/path/to/genome2.fasta,/path/to/annotation2.gff3 species_3,GCF_000000003.1 species_4,,/path/to/genome4.fasta,/path/to/annotation4.gff3 ``` ### Run the pipeline Run the pipeline using: ```bash nextflow run nf-core/genomeqc \ -profile \ --input samplesheet.csv \ --outdir ``` You can run the pipeline using a test profile and docker: ```bash nextflow run nf-core/genomeqc -profile test,docker --outdir ./results ``` > [!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](https://nf-co.re/docs/running/run-pipelines#using-parameter-files). For more details and further functionality, please refer to the [usage documentation](https://nf-co.re/genomeqc/usage) and the [parameter documentation](https://nf-co.re/genomeqc/parameters). ## Pipeline output To see the results of an example test run with a full size dataset refer to the [results](https://nf-co.re/genomeqc/results) tab on the nf-core website pipeline page. For more details about the output files and reports, please refer to the [output documentation](https://nf-co.re/genomeqc/output). ## Credits nf-core/genomeqc was originally written by [Chris Wyatt](https://github.com/chriswyatt1) and [Fernando Duarte](https://github.com/FernandoDuarteF) at the University College London. We thank the following people for their extensive assistance in the development of this pipeline: - [Mahesh Binzer-Panchal](https://github.com/mahesh-panchal) ([National Bioinformatics Infrastructure Sweden](https://nbis.se/)) - [Usman Rashid](https://github.com/GallVp) ([The New Zealand Institute for Plant and Food Research](https://www.plantandfood.com/en-nz/)) - [Lauren Huet](https://github.com/LaurenHuet) ([Schmidt Ocean Institute](https://schmidtocean.org/)) - [Stephen Turner](https://github.com/stephenturner/) ([Colossal Biosciences](https://colossal.com/)) - [Felipe Perez Cobos](https://github.com/fperezcobos) ([Institute of Agrifood Research and Technology](https://www.irta.cat/en/)) - [Simon Murray](https://github.com/SimonDMurray) ([Nextflow Ambassador](https://www.nextflow.io/our_ambassadors.html)) ## Contributions and Support If you would like to contribute to this pipeline, please see the [contributing guidelines](docs/CONTRIBUTING.md). For further information or help, don't hesitate to get in touch on the [Slack `#genomeqc` channel](https://nfcore.slack.com/channels/genomeqc) (you can join with [this invite](https://nf-co.re/join/slack)). ## Citations 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: > **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](https://dx.doi.org/10.1038/s41587-020-0439-x).

License
MIT

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