Introduction

ecoflow/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 raw files or Refseq IDs), and runs commonly used tools to assess their quality.

There are three different ways you can run this pipeline:

1. Genome only
2. Annotation only
3. Genome and Annotation.

Currently, only Genome plus Annotation is functional

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...
4. Extracts longest protein isoform: GffRead.
5. Finds orthologous genes: Orthofinder.
6. Plots an orthology-based phylogenetic tree : Tee Summary, as well as other relevant stats from the above steps.
7. Summary with MultiQC.

2. Genome Only (in development):

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.
   4. QUAST: Computes contiguity and integrity statistics: N50, N90, GC%, number of sequences.
3. Summary with MultiQC.

3. Annnotation Only (in development):

1. Downloads the gene annotation files from NCBI: NCBI genome download - Or you provide your own annotations.
2. Describes your annotation : AGAT: Gene, feature, length, averages, counts.
3. 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 single copy markers.

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, leaving the rest of the fields empty:

species,refseq,fasta,gff,fastq
Homo_sapiens,,/path/to/genome.fasta,/path/to/annotation.gff3,
Gorilla_gorilla,,/path/to/genome.fasta,/path/to/annotation.gff3,
Pan_paniscus,,/path/to/genome.fasta,/path/to/annotation.gff3,

When running on --genome_only mode, you can leave the gff field empty. Otherwise, this field will be ignored.

2. Refseq IDs

Additionally, you can run the pipeline using the Refseq IDs of the assemblies of interest in the refseq field, leaving the rest of the fields empty:

species,refseq,fasta,gff,fastq
Pongo_abelii,GCF_028885655.2,,,
Macaca_mulatta,GCF_003339765.1,,,

Run the pipeline

Run the pipeline using:

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:

nextflow run nf-core/genomeqc -profile 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

ecoflow/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)

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" --project_name "DToL" --data_status "Mapped Reads - Done" --experiment_type "Chromium genome" --download_location "/Users/raheela/Documents" --download_option "assemblies" --species_list "Apamea sordens,Bufo bufo"