PhiSpy 3.7.6

Prophage finder using multiple metrics

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 ([e-mail]) 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.

1. Python - version 3.4 or later
2. Biopython - version 1.58 or later
3. 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.

1. 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.

2. 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.

3. 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