Prophage finder using multiple metrics
Project description
INTRODUCTION
PhiSpy is a computer program written in C++ and Python to identify prophages in a complete bacterial genome sequences.
Initial versions of PhiSpy were written by
Sajia Akhter (sajia@stanford.edu) PhD Student Edwards Bioinformatics Lab (http://edwards.sdsu.edu/labsite/) Computational Science Research Center (http://www.csrc.sdsu.edu/csrc/) San Diego State University (http://www.sdsu.edu/)
Improvements, bug fixes, and other changes were made by
Katelyn McNair Edwards Bioinformatics Lab San Diego State University
Przemyslaw Decewicz University of Warsaw
SYSTEM REQUIREMENTS
The program should run on Mac and Unix platforms, although it was not tested in all platforms.
SOFTWARE REQUIREMENTS
PhiSpy requires following programs to be installed in the system. NOTE: You can ignore this if you're using the singularity container method of installation.
- Python - version 3.4 or later
- Biopython - version 1.58 or later
- gcc - GNU project C and C++ compiler - version 4.4.1 or later
INSTALLATION
For most users, this will create a local installation for you
git clone https://github.com/linsalrob/PhiSpy.git
cd PhiSpy`
python3 setup.py install --user
If you have root and you want to install globally, you can change the setup command.
git clone https://github.com/linsalrob/PhiSpy.git
cd PhiSpy`
python3 setup.py install
For ease of use, you may wish to add the location of PhiSpy.py to your $PATH.
TO TEST THE PROGRAM
Change to the install location and run PhiSpy with an example genome:
% cd PhiSpy`
% python3 PhiSpy.py -o output_directory -t data/trainSet_160490.61.txt tests/Streptococcus_pyogenes_M1_GAS.gb
We use the GenBank
format file for Streptococcus pyogenes M1 GAS that we hvae provided in the tests/
directory, and we use the training set for S. pyogenes M1 GAS that we have pre-calculated. This quickly identifies the four prophages in this genome, runs the repeat finder on all of them, and outputs the answers.
You will find the output files from this query in output_directory
.
TO RUN PHISPY
The simplest command is:
% python3 PhiSpy.py -f genbank_file -o output_directory
where:
genbank file
: The input DNA sequence file in GenBank format.output directory
: The output directory is the directory where the final output file will be created.
If you have new genome, we recommend annotating it using the RAST server or PROKKA.
After annotation, you can download the genome directory from the server.
HELP
For the help menu use the -h
option:
% python PhiSpy.py -h
OUTPUT FILES
There are 3 output files, located in output directory.
-
prophage.tbl: This file has two columns separated by tabs [id, location]. The id is in the format: pp_number, where number is a sequential number of the prophage (starting at 1). Location is be in the format: contig_start_stop that encompasses the prophage.
-
prophage_tbl.tsv: This is a tab seperated file. The file contains all the genes of the genome. The tenth colum represents the status of a gene. If this column is 1 then the gene is a phage like gene; otherwise it is a bacterial gene.
This file has 16 columns:(i) fig_no: the id of each gene; (ii) function: function of the gene; (iii) contig; (iv) start: start location of the gene; (v) stop: end location of the gene; (vi) position: a sequential number of the gene (starting at 1); (vii) rank: rank of each gene provided by random forest; (viii) my_status: status of each gene based on random forest; (ix) pp: classification of each gene based on their function; (x) Final_status: the status of each gene. For prophages, this column has the number of the prophage as listed in prophage.tbl above; If the column contains a 0 we believe that it is a bacterial gene. If we can detect the att sites, the additional columns will be: (xi) start of attL; (xii) end of attL; (xiii) start of attR; (xiv) end of attR; (xv) sequence of attL; (xvi) sequence of attR.
- prophage_coordinates.tsv: This file has the prophage ID, contig, start, stop, and potential att sites identified for the phages.
EXAMPLE DATA
We have provided two different example data sets.
- Streptococcus pyogenes M1 GAS which has a single genome contig. The genome contains four prophages.
To analyze this data, you can use:
python3 PhiSpy.py -o output_directory -t data/trainSet_160490.61.txt tests/Streptococcus_pyogenes_M1_GAS.gb
And you should get a prophage table that has this information (for example, take a look at output_directory/prophage.tbl
).
Prophage number | Contig | Start | Stop |
---|---|---|---|
pp_1 | NC_002737 | 529631 | 569288 |
pp_2 | NC_002737 | 778642 | 820599 |
pp_3 | NC_002737 | 1192630 | 1222549 |
pp_4 | NC_002737 | 1775862 | 1782822 |
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