A Snakemake workflow to automate and facilitate identification of synteny and orthology using GENESPACE.
The aim of this workflow is to make the use of GENESPACE easier. It does so by automating the most annoying parts of a GENESPACE analysis, namely:
- Input data formating
- Software instalation
Input data formating is the "trickiest part of running GENESPACE" (see GENESPACE section 3). With the snake-GENESPACE workflow you can have your data as GFF structural annotations and fasta genome assemblies. The workflow automatically:
- Converts the GFF file into bed format.
- Extracts and translates coding sequences into peptide fasta files.
- Renames each bed and fasta entry to have the exact same (gene) name.
This is done with the brilliant AGAT suite of tools and some custom awk script. You can also have part or all of your data already in the right format for GENESPACE. In this case you can include it in the snake-GENESPACE input directory (details below). Even if all your data is in the right format you might still want to use snake-GENESPACE to install all the required softwares.
GENESPACE depends on the stand alone tools MCScanX and Orthofinder as well as a number of R-packages. It can be frustrating to manage installation of all the dependecies. Snakemake makes such dependencies easy to deal with by installing them automatically in a conda environment. All this means is that you just need to install Snakemake via Conda and to git clone this repository to have all the GENESPACE requirement met.
- install Snakemake via Conda.
- git clone snake-GENESPACE:
git clone https://github.com/kenji-yt/snake-GENESPACE.git
The input to snake-GENESPACE is a directory. Inside it you should have one directory for each species (or genome). The name of the directory should be the species or genome name and will appear as such in the GENESPACE output figures. In these directories you should have only two files: a gff annotation and a fasta assembly. Name these files as you wish as long as they have one of the following extensions: "gff","gff3","fa","fasta","fq","fna","fastq".
If you have some data already in the right format for GENESPACE just put your "bed" and "peptide" directories within the snake-GENESPACE input directory. In brief, GENESPACE requires an annotation in bed format and a fasta file with peptide sequences. The gene or feature names in the bed file should match the sequence names in the fasta exactly. All bed files should be put in a directory called "bed" and all fasta files in a directory called "peptide". The name of each file should be the desired species (or genome) name and should be the same for corresponding bed and fasta. Getting data in this format is what snake-GENESPACE does using AGAT and custom bash and awk script (see "snake-GENESPACE/workflow/scripts/parse_genespace_input.sh").
Your input directory should have the following structure:
Input_directory/
├── Species_1/
│ ├── annotation.gff
│ └── assembly.fa
├── Species_2/
│ ├── annotation.gff
│ └── assembly.fa
├── peptide/
│ ├── Species_3.fa
│ └── Species_4.fa
└── bed/
├── Species_3.bed
└── Species_4.bed
Once you have your input directory you just need to edit "snake-GENESPACE/config/config.yaml". This file is used to tell snake-GENESPACE where the input directory is and where the output should be written to. So just replace the paths after "INPUT:" and "OUTPUT:" with the path to your input directory and the path to a new directory that will be created to house the outputs. Note that these paths should be either absolute or relative to the "snake-GENESPACE/" directory.
That's it, you are ready to run a GENEPSACE analysis. Just activate your conda environment where snakemake is installed (eg. "conda activate snakemake_env") and then, from within the "snake-GENESPACE/" directory run:
snakemake --use-conda --cores N
Make sure to be in the conda directory with snakemake intalled and to replace N with the number of cores you wish to allocate to snakemake.
Extra: If you are new to snakemake you might find it weird to run the program from within its source directory. This is how snakemake works and it's nothing to worry about. Finally, do not be alarmed if the messages printed to the terminal are confusing. This is normal since multiple processes print out at the same time (if -c >1). If you want to know what happened check out the log files in the log directory within your specified output directory.