INTRODUCTION

PhiSpy is a computer program written in C++, Python and R to identify prophages in a complete bacterial genome sequences.

This version here is a modification of the original version of PhiSpy. We improved and fix some bugs and add additional features.

Example:

• python2 -> python3
• implementation as a module
• output as gff3

HISTORY

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 (http://edwards.sdsu.edu/labsite/) San Diego State University (http://www.sdsu.edu/)

Jose F. Sanchez Herrero, Bioinformatics Unit IGTP, Hospital German Trias i Pujol (http://www.germanstrias.org/technology-services/genomica-bioinformatica/)

SYSTEM REQUIREMENTS

The program should run on all Unix platforms, although it was not tested in all platforms.

SOFTWARE REQUIREMENTS

The modified version here does not contain any new module or dependency so the same sotware requirements as the original software are expected.

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 - 3.5 later
2. Biopython - version 1.58 or later
3. gcc - GNU project C and C++ compiler - version 4.4.1 or later
4. The R Project for Statistical Computing - version 2.9.2 or later
5. Package randomForest in R - version 4.5-36 or later

INSTALLATION

1. Clone this repository
2. % cd PhiSpy
3. % make
4. For ease of use, add the location of PhiSpy.py to your $PATH.

TO TEST THE PROGRAM

Within the test_data folder, we have included a simple script that it unzip file and generate calls for both examples provided.

1. % cd PhiSpy/test_data
2. % python test.py

You will find the output files of this genome at output_directory.

TO RUN PHISPY

% ./PhiSpy.py -i organism_directory -o output_directory -c

where: 'output directory': Output directory is the directory where the final output file will be created.

'organism directory': The seed annotation directory for the input bacterial organism whose prophage(s) need to be identified.

You can download the SEED genomes from the PhAnToMe database

Or, If you have new genome, you can annotate it using the RAST server. After annotation, you can download the genome directory from the server.

Or, If you have the GenBank file (containing sequence) of the genome, you can convert it using the following command: % python PhiSpy_tools/genbank_to_seed.py GenBank_file.gb organism_directory

Now to run PhiSpy, use organism_directory as 'organism directory'.

The program will access the following files in the organism_directory: i. contig file: organism_directory/contigs ii. tbl file for peg: organism_directory/Features/peg/tbl iii. assigned_functions file: organism_directory/assigned_functions or organism_directory/proposed_functions or organism_directory/proposed_non_ff_functions
iv. tbl file for rna: organism_directory/Features/rna/tbl

Note: The assigned functions file may not be in the RAST genome directory. You can create it from proposed_functions and proposed_non_ff_functions or you can use this perl script to create an assigned_functions file for you.

REQUIRED INPUT OPTIONS

The program will take 1 command line input.

It shows a list (run with -c option) and asks for a number from the list. In the list, there are several organisms and each organism is associated by a number. If you find a closely related genome of your interested organism enter the number. PhiSpy will consider that genome as training genome. Otherwise, enter 0 to run with generic training set.

HELP

For the help menu use the -h option: % python PhiSpy.py -h

OUTPUT FILES

There are 4 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.

#prophage number	contig	start	stop
pp_1	NC_002737	529631	604720
pp_2	NC_002737	778642	846824
pp_3	NC_002737	1191309	1255536
pp_4	NC_002737	1607352	1637214

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.

fig_no	function	contig	start	stop	position	rank	my_status	pp	Final_status	start of attL	end of attL	start of attR	end of attR	sequence of attL	sequence of attR	Reason for att site
gene 1	Chromosomal replication initiator protein DnaA	NC_002737	232	1587	1	0.07398152869335141	0	0	0
gene 2	DNA polymerase III beta subunit (EC 2.7.7.7)	NC_002737	1742	2878	2	0.07106037747241106	0	0	0
gene 3	R801 tRNA-Arg	NC_002737	2953	3150	3	0.06827053181260112	0	0	0

3. prophage_coordinates.csv: This file has the prophage ID, contig, start, stop, and potential att sites identified for the phages.

prophage_ID	Contig	Start	End	attL_Start	attL_End	attR_Start	attR_End	attL_Seq	attR_Seq	Longest_Repeat_flanking_phage
pp1	NC_002737	87661	119067	87232	87245	117100	117113	aaacttgataact	agttatcaagttt	Longest Repeat flanking phage and within 2000 bp
pp2	NC_002737	529631	605856	529660	529672	604721	604733	ccatagtaacct	aggttactatgg	Longest Repeat flanking phage and within 2000 bp
pp3	NC_002737	778642	840502	777439	777452	840272	840285	taaaacgtctttg	taaaacgtctttg	Longest Repeat flanking phage and within 2000 bp
pp4	NC_002737	1191309	1241894	1189734	1189747	1243163	1243176	atgtctaaatcaa	ttgatttagacat	Longest Repeat flanking phage and within 2000 bp

4. prophage.gff3: This file contains the information provided under prophage_coordinates.csv in gff3 format in order to standarize results and visualization.

##gff-version 3	----	----	----	----	----	----	----	----
NC_002737	PhiSpy	prophage_region	87661	119067	.	.	.	ID=pp1
NC_002737	PhiSpy	attL	87232	87245	.	.	.	ID=pp1
NC_002737	PhiSpy	attR	117100	117113	.	.	.	ID=pp1
NC_002737	PhiSpy	prophage_region	529631	605856	.	.	.	ID=pp2
NC_002737	PhiSpy	attL	529660	529672	.	.	.	ID=pp2
NC_002737	PhiSpy	attR	604721	604733	.	.	.	ID=pp2
NC_002737	PhiSpy	prophage_region	778642	840502	.	.	.	ID=pp3
NC_002737	PhiSpy	attL	777439	777452	.	.	.	ID=pp3
NC_002737	PhiSpy	attR	840272	840285	.	.	.	ID=pp3
NC_002737	PhiSpy	prophage_region	1191309	1241894	.	.	.	ID=pp4
NC_002737	PhiSpy	attL	1189734	1189747	.	.	.	ID=pp4
NC_002737	PhiSpy	attR	1243163	1243176	.	.	.	ID=pp4

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.

• Salmonella enterica serovar Enteritidis LK5

This is an early draft of the genome (the published sequence has a single contig), but this draft has 1,410 contigs and some phage like regions.

If you run PhiSpy on this draft genome with the default parameters you will not find any prophage because they are all filtered out for not having enough genes. By default, PhiSpy requires 30 genes in a prophage. You can alter that stringency on the command line, and for example reducing the phage gene window size to 10 results in 3 prophage regions being identified.

python PhiSpy.py -t 21 -w 10 -i Test_Organism/272989.13/ -o Test_Organism/272989.13.output

LICENSE

This is a modified version of the original code. No further developments were made, only conversion from python2 to python3 and small bug fixes were done. Please refer to the original version for further details and cited them accordingly.

The MIT License (MIT)

Copyright (c) 2016 Rob Edwards

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.