CHERRY is a python library for predicting the interactions between viral and prokaryotic genomes. CHERRY is based on a deep learning model, which consists of a graph convolutional encoder and a link prediction decoder.
In this program, we provide a simplified version of CHERRY, which only used the CRISPRs information in CHERRY's graph for host prediction. In addition, in this lite version, we provide a more easier way to predict the links between bacterial contigs and phage contigs. The sketch of CHERRY-crispr is shown as below:
Input (provided by user):
1. bacterial contigs from their samples (FASTA files)
2. phage contigs from their samples (FASTA files)
Output:
The links (interactions) between bacteria and phages (CSV files)
- Python 3.x
- Pandas
- Numpy
- Biopython
- NCBI BLAST+
We suggest you to install all the package using conda (both miniconda and Anaconda are ok) following the command lines as below:
conda create --name cherry_crispr python=3.8
conda activate cherry_crispr
conda install pandas numpy biopython
conda install blast -c bioconda
Once install the required environments, you need to activate it when you want to use:
conda activate cherry_crispr
Then, the commond of CHERRY-crispr can be called by:
python PATH_TO_CHERRY_CRISPR/cherry_crispr.py --bfolder PATH_TO_BACTERIA --pfile PATH_TO_PHAGE --ident IDENTITY_THRESHOLD --threads NUM_OF_THREAD --rootpth PATH_TO_OUTPUT --dbdir PATH_TO_CHERRY_CRISPR/database
OR
python PATH_TO_CHERRY_CRISPR/cherry_crispr.py --bfile PATH_TO_BACTERIA --pfile PATH_TO_PHAGE --ident IDENTITY_THRESHOLD --threads NUM_OF_THREAD --rootpth PATH_TO_OUTPUT --dbdir PATH_TO_CHERRY_CRISPR/database
There are two options for bacterial contigs:
-
--bfolder: the folder where you store your bacterial contigs (all the contigs should be FASTA files)
-
--bfile: the file where you store your bacterial contigs (FASTA file)
For example:
python CHERRY_crispr/cherry_crispr.py --bfolder ~/bacteria/ --pfile ~/phage.fa --threads 40 --rootpth ~/test_dir --dbdir CHERRY_crispr/database
OR
python CHERRY_crispr/cherry_crispr.py --bfile ~/bacteria.fa --pfile ~/phage.fa --threads 40 --rootpth ~/test_dir --dbdir CHERRY_crispr/database
There are three output files in --rootpth PATH_TO_OUTPUT.
- CRISPRs.fa: CRISPRs found in your provided bacteria FASTA
- crispr_align.txt: BLASTN results between CRISPR and phage
- cherry_crispr_pred.csv: CSV files of the prediction (alignment >
--ident IDENTITY_THRESHOLD)
If you use this program, please cite the following papers:
- CHERRY:
Jiayu Shang, Yanni Sun, CHERRY: a Computational metHod for accuratE pRediction of virus–pRokarYotic interactions using a graph encoder–decoder model, Briefings in Bioinformatics, 2022;, bbac182, https://doi.org/10.1093/bib/bbac182
- CRT:
Bland C, Ramsey TL, Sabree F, Lowe M, Brown K, Kyrpides NC, Hugenholtz P:
CRISPR Recognition Tool (CRT): a tool for automatic detection of clustered regularly interspaced palindromic repeats. BMC Bioinformatics. 2007 Jun 18;8(1):209
The original version of CHERRY can be found via: CHERRY
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent