Introduction

nf-core/genomeqc is a bioinformatics pipeline that compares the quality of multiple genomes, along with their annotations.

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 provided inputs, 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)

2. Genome Only: 1. Downloads the genome files from NCBI: NCBI genome download - Or you provide your own genomes 2. Describes genome assembly: 1. BUSCO: Evaluates genome completeness based on single copy markers. 2. BUSCO Ideogram: Plots the location of markers on the assembly. 3. tidk (optional): Indetfies and visualises telomeric repeats. 3. QUAST: Computes contiguity and integrity statistics: N50, N90, GC%, number of sequences. 3. Summary with MultiQC.

1. Genome and Annotation: 1. Downloads the genome and gene annotation files from NCBI: NCBI genome download - Or you provide your own genomes/annotations 2. Describes genome assembly: 1. BUSCO: Evaluates genome completeness based on single copy markers. 2. BUSCO Ideogram: Plots the location of markers on the assembly. 3. Merqury (optional): Evaluates genome completeness based on sequencing reads. 4. tidk (optional): Indetifies and visualises telomeric repeats. 5. QUAST: Computes contiguity and integrity statistics: N50, N90, GC%, number of sequences. 6. More options... 3. Describes annotation : 1. AGAT: Number of genes, features, length... 2. Gene Overlaps: Finds the number of overlapping genes. 3. More options... 5. Extracts longest protein isoform: GffRead. 6. Finds orthologous genes: Orthofinder. 7. Plots an orthology-based phylogenetic tree : Tee Summary, as well as other relevant stats from the above steps. 8. Summary with MultiQC.

[!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 on how to set-up Nextflow. Make sure to test your setup 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,refseq,fasta,gff,fastq species_1,,/path/to/genome.fasta,/path/to/annotation.gff3, species_2,,/path/to/genome.fasta,/path/to/annotation.gff3, species_3,,/path/to/genome.fasta,/path/to/annotation.gff3,

2. ncbi accessions

Additionally, you can run the pipeline using providing ncbi accessions (RefSeq or GenBank, depeding on the mode you wish to run) in the ncbi field:

csv species,refseq,fasta,gff,fastq species_1,GCF_000000001.1,,, species_2,GCF_000000002.1,,, species_3,GCF_000000003.1,,,

Run the pipeline

Run the pipeline using:

bash nextflow run nf-core/genomeqc \ -profile <docker/singularity/.../institute> \ --input samplesheet.csv \ --outdir <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.

Pipeline output

To see the results of an example 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/genomeqc was originally written by Chris Wyatt and Fernando Duarte at the University College London.

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

• Mahesh Binzer-Panchal (National Bioinformatics Infrastructure Sweden)
• Usman Rashid (The New Zealand Institute for Plant and Food Research)
• Lauren Huet (Schmidt Ocean Institute)
• Stephen Turner (Colossal Biosciences)
• Felipe Perez Cobos (Institute of Agrifood Research and Technology)
• Simon Murray (Nextflow Ambassador)

Contributions and Support

If you would like to contribute to this pipeline, please see the contributing guidelines.

Citations

An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md file.

This pipeline uses code and infrastructure developed and maintained by the nf-core community, reused here under the MIT license.

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.

python app/downloader-utility.py --clade "Chordata" --projectname "DToL" --datastatus "Mapped Reads - Done" --experimenttype "Chromium genome" --downloadlocation "/Users/raheela/Documents" --downloadoption "assemblies" --specieslist "Apamea sordens,Bufo bufo"