kennthshang / cherry_crispr_multihost

multihost version of CHERRY

CHERRY-crispr version

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 an extension version of CHERRY, which uses the CRISPR information in CHERRY's database for multi-host (host range) prediction.

Input (provided by the user):
    1. phage contigs from their samples (FASTA files)

Output:
    The host range of the given phages (CSV files)

Required Dependencies

• Python 3.x
• Pandas
• Numpy
• Biopython
• NCBI BLAST+

An easiler way to install

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_multihost python=3.8
conda activate cherry_crispr_multihost

conda install pandas numpy biopython
conda install blast -c bioconda

Usage

Once install the required environment, you need to activate it when you want to use:

conda activate cherry_crispr_multihost

Then, the command of multi-host extension can be called by:

python PATH_TO_cherry_crispr_multihost/Cherry_multihost.py --infile PATH_TO_FASTA --outfolder PATH_TO_OUTPUT_FOLDER --datasetpth [where you place the dataset folder provided in this GitHub] --threads NUM_OF_THREAD --ident IDENTITY_OF_ALIGNMENT --coverage COVERAGE_OF_ALIGNMENT

# example
python CHERRY_crispr_multihost/Cherry_multihost.py --infile nucl.fasta --outfolder test_out/ --datasetpth CHERRY_crispr_multihost/dataset --ident 75 --coverage 0.75

There are two thresholds for users:

1. --ident: the identity of the CRISPRs alignments (default: 75)
2. --coverage: the coverage of the CRISPRs alignments (default: 0.75)

Outputs

There are two output files in --outfolder PATH_TO_OUTPUT_FOLDER.

1. alignment_result.tab: BLASTN results between CRISPR and phage
2. prediction.csv: CSV files of the prediction (alignment > --ident IDENTITY_OF_ALIGNMENT && > --coverage COVERAGE_OF_ALIGNMENT)

Citation

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

The original version of CHERRY can be found via: CHERRY

cherry_crispr_multihost's Issues

Difference in the number of CHERRY_crispr_multihost and CHERRY prediction results

Dear KennthShang,

I hope this email finds you well. I am reaching out to you regarding your open-source project and have a question regarding the difference in predicting the number of virus hosts using CHERRY_crispr_multihost.py and Cherry_single.py in PhaBOX.

I have noticed that when running CHERRY_crispr_multihost.py and Cherry_single.py with their default parameters, they provide different results. Specifically, CHERRY_crispr_multihost.py yields a lower number of host predictions whereas Cherry_single.py produces the opposite results. I only counted the number based on crispr.

Cherry_single.py Result
cut -f5 -d , host_prediction.csv |sort |uniq -c
    112 -
   2989 CRISPR
    170 Predict

CHERRY_crispr_multihost Result
$wc -l prediction.csv 
2566 prediction.csv

Additionally, I would like to inquire whether the values used in Cherry_multihost.py for "--ident" (the identity of the CRISPR alignments) with a default of 75, and "--coverage" (the coverage of the CRISPR alignments) with a default of 0.75, might be too low. Is it necessary for me to increase these threshold values, and if so, should I make adjustments in Cherry_single.py as well?

I truly appreciate your contributions to the open-source community, and I am very interested in your project. I would greatly appreciate any insights you can provide to help me better understand this discrepancy.

Thank you for your time and response.

Best regards,
Robin