Script to assign taxonomy to a bacteriophage at the genus and species level
Project description
taxmyPHAGE
Developed by Andrew Millard , Thomas Sicheritz-Ponten and Remi Denise
Script to assign taxonomy to a bacteriophage at the genus and species level. It will identify the most similar genomes in the set of currently classified ICTV genomes that are present in the VMR. Read about the VMR here. It will compare the query genome against these genomes and run a VIRIDIC-like analysis on the closest relatives. Interpret the output of VIRIDIC-like analysis to determine if the phage falls within a current genus and or species. It does not run VIRIDIC, but utilises the same formula for comparison of genomes. The input is a single genome sequence. The remainder of the analysis is automated
Designed for:
- Individual complete phage genomes
What it will do:
- Classify a dsDNA phage genomes at the Genus and or species level against ICTV genomes
- Tell you if your genome represents a new genus
- Use current ICTV cutoffs for Genera and Species
- accept multiple inputs at the same time
What it wont do:
- Metagenomic samples
- Eukaryotic viruses
- RNA phages - it will give a result - not necessarily the correct one
- ssDNA phages - again a result but likely not accurate
- Classify a phage into a new family
- Compare against every single phage genome in Genbank. It is designed for classification , so compares against currently classified phages.
A web version will be available soon.
QUICK start and test
mamba create -n taxmyphage -c conda-forge -c bioconda taxymyphage
mamba activate taxmyphage
python tax_myPHAGE.py -i test.fna -t 8
This should check the required software is installed and give a warning if not. It will also download the required fasta database and MASH file for comparison. These will be installed in the cloned tax_myPHAGE directory. If you download manually then please move them into tax_myPHAGE directory.
Output of the test should have the following lines at the bottom
Requirements
It can be run on a standard laptop in a reasonable time.
Input Files | Description | Download Instructions |
---|---|---|
ICTV.msh (MASH index) |
Prebuilt MASH index of ICTV genomes. Download here | Download: wget https://millardlab-inphared.s3.climb.ac.uk/ICTV_2023.msh |
Bacteriophage_genomes.fasta.gz |
Database of ICTV-classified genomes. Download here. | - Download: wget https://millardlab-inphared.s3.climb.ac.uk/Bacteriophage_genomes.fasta.gz - Unzip: gunzip Bacteriophage_genomes.fasta.gz - Create blast db: makeblastdb -in Bacteriophage_genomes.fasta -parse_seqids -dbtype nucl |
VMR.xlsx |
Virus Metadata Resource (VMR) included. | - Download: wget https://ictv.global/vmr/current |
Install
Conda
mamba install -c conda-forge -c bioconda taxmyphage
pip
pip install taxmyphage
If you installing by pip, don't forget to install a working version of mash and blast
Run with
Quick start
taxmyphage -i input.fasta
Options
optional arguments:
-h, --help show this help message and exit
-V, --version Show the conda-prefix-replacement version number and exit.
-v, --verbose
General options:
-i [FASTA_FILE ...] [[FASTA_FILE ...] ...], --input [FASTA_FILE ...] [[FASTA_FILE ...] ...]
Path to an input fasta file(s), or directory containing fasta files. The fasta file(s) could contain multiple phage genomes. They can be compressed (gzip). If a directory is given the
expected fasta extentions are ['fasta', 'fna', 'fsa', 'fa'] but can be gzipped. (Required)
-o OUTPUT, --output OUTPUT
Path to the output directory. (Default is current directory)
-p PREFIX, --prefix PREFIX
will add the prefix to results and summary files that will store results of MASH and comparision to the VMR Data produced by ICTV combines both sets of this data into a single csv file.
Use this flag if you want to run multiple times and keep the results files without manual renaming of files. (Default no prefix)
-d DIST, --distance DIST
Will change the mash distance for the intial seraching for close relatives. We suggesting keeping at 0.2 If this results in the phage not being classified, then increasing to 0.3 might
result in an output that shows the phage is a new genus. We have found increasing above 0.2 does not place the query in any current genus, only provides the output files to demonstrate it
falls outside of current genera. (Default is 0.2)
--no-figures Use this option if you don't want to generate Figures. This will speed up the time it takes to run the script - but you get no Figures. (By default, Figures are generated)
-t THREADS, --threads THREADS
Maximum number of threads that will be used by BLASTn. (Default is 1)
Options related to the database:
--db_folder FOLDER_PATH
Path to the database directory where the databases are stored. (Default is /Users/rdenise/Documents/Scripts/tax_myPHAGE_github_version/taxmyphage/database)
Install folder and database options:
--install Use this option to download and install the databases. (Default is False)
Executable options, if not in PATH:
--blastcmd BLASTCMD Path to the blastn executable (default: blastcmd)
--blastn BLASTN Path to the blastn executable (default: blastn)
--makeblastdb MAKEBLASTDB
Path to the blastn executable (default: makeblastdb)
--mashexe MASHEXE Path to the MASH executable (default: mash)
Indicative run time
The time to classify a phage will depend on the number of hits and number of phages currently classified within a particular genus. The more species within a genus, the longer the time for classification. The numbers below are from running on a 16 core server. We have been running the process on a MAC book and Windows laptop in reasonable time periods.
Genus | Number of genomes in Genera | Time(H:M:S) |
---|---|---|
Cheoctovirus | 96 | 00:07:44 |
Tequatrovirus | 83 | 00:26:19 |
Peduovirus | 27 | 00:00:23 |
Warwickvirus | 18 | 00:00:18 |
Pseudotevenvirus | 9 | 0:01:15 |
Changmaivirus | 2 | 0:00:17 |
Stompvirus | 1 | 0:00:16 |
Output files
[output_folder] <- General output folder
└── [genome query_id] <- Results output for the genome query_id
├── Output_of_taxonomy.csv <- Output of the taxonomy classification
├── Summary_file.txt <- Summary of the analysis (summarises what was printed to screen )
├── heatmap.pdf <- Heatmap of the similarity to the closest relatives (pdf)
├── heatmap.png <- Heatmap of the similarity to the closest relatives (png)
├── heatmap.svg <- Heatmap of the similarity to the closest relatives (svg)
├── known_taxa.fa <- Fasta file of the closest relatives
├── mash.txt <- Output of the MASH analysis
├── query.fasta <- Input fasta file
├── similarities.tsv <- Similarities to the closest relatives
├── top_right_matrix.tsv <- Top right matrix of similarity to closest relatives (same as heatmap)
└── viridic <- VIRIDIC-like analysis
├── viridic_in.fa <- Input fasta file
├── viridic_in.fa.blastn_vs2_self.tab.gz <- Blastn output of the input fasta file against itself
├── viridic_in.fa.genus_species_clusters.tsv <- Clusters of the closest relatives
├── viridic_in.fa.ndb <- Blastn database of the closest relatives
├── viridic_in.fa.nhr
├── viridic_in.fa.nin
├── viridic_in.fa.njs
├── viridic_in.fa.not
├── viridic_in.fa.nsq
├── viridic_in.fa.ntf
└── viridic_in.fa.nto
Output files explained
- Summary_file.txt - Summarises what was printed to screen
Query sequence header was:test1
Query sequence can be classified within a current genus and represents a new species, it is in:
Class:Caudoviricetes Family: Not Defined Yet Subfamily:Vequintavirinae Genus:Certrevirus Species:name_your_species
-
Output_of_taxonomy.csv - Provides Cluster and Species numbers for you query phage, merged with data from the VMR for the closest relatives to you query
-
***pdf, svg, png - image files of top right matrix of similarity to closest currently classified phages
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