Scripts to make a concatenated alignment of core genes from bacterial genomes and compare gene content.
Scripts from this repository have been used in the following manuscripts:
Mortimer TD, Weber AM, Pepperell CS. 2016. Evolutionary thrift: mycobacteria repurpose plasmid diversity during adaptation of type VII secretion systems. bioRxiv:67207.
Dang UJ, Devault AM, Mortimer TD, Pepperell CS, Poinar HN, Golding GB. 2016. Estimation of Gene Insertion/Deletion Rates with Missing Data. Genetics:genetics.116.191973.
Shapiro LR, Scully ED, Straub TJ, Park J, Stephenson AG, Beattie GA, Gleason ML, Kolter R, Coelho MC, Moraes CMD, et al. 2016. Horizontal Gene Acquisitions, Mobile Element Proliferation, and Genome Decay in the Host-Restricted Plant Pathogen Erwinia Tracheiphila. Genome Biol Evol 8:649–664.
O’Neill MB, Mortimer TD, Pepperell CS. 2015. Diversity of Mycobacterium tuberculosis across Evolutionary Scales. PLoS Pathog 11:e1005257.
###RunProkka.ipy This script runs the annotations program Prokka on a directory of fasta format genomes. Each genome will hava a directory as output. Additionally, a directory containing protein sequences in fasta format for each genome will be created as well as a directory containing the corresponding nucleotide sequences.
Requirements: IPython, Prokka (http://www.vicbioinformatics.com/software.prokka.shtml)
Current Versions: IPython v 0.13.1, Prokka v 1.7
Usage: RunProkka.ipy [fasta directory]
###RunOrthoMCL.py
This script runs the program OrthoMCL to put proteins from annotated genomes
into orthologous groups. A sql database must be created and empty for this
program to run correctly. Details of the database should be provided in the
OrthoMCL config file. Additionally, the directory where the annotated proteins
are located should be provided to this script.
Requirements: OrthoMCL (http://orthomcl.org/orthomcl/)
Current Versions: Python 2.7.3, OrthoMCL v 2.0.9
Usage: RunOrthoMCL.py -t [# of threads] [OrthoMCL config file] [directory of proteins]
###FilterOrthoMCLGroups.py
This script filters protein groups output from OrthoMCL and returns those that contain only one protein per genome and have all genomes represented (the core proteins).
Usage: FilterOrthoMCLGroups.py -g [input groups file] -n [number of genomes]
###coreGenomeAlignment.py
This script makes a core genome alignment from proteins in a groups file in the format output by OrthoMCL. FilterOrthoMCLGroups.py should be used first. The script should be provided with fasta files of DNA or amino acid sequences for proteins located in one directory.
Requirements: Biopython, MAFFT, trimAl(http://trimal.cgenomics.org/), translatorX (http://www.translatorx.co.uk/)
Current Versions: Python 2.7.3, Biopython v 1.63, MAFFT v 7.130b, trimAl v 1.3
Usage: coreGenomeAlignment.py -t [# of threads] [input groups file] [directory with sequences]
###GeneMLTrees.ipy
This script produces maximum likelihood trees for a group of gene alignments stored in a directory. The script is designed to use output from MakeCoreGenomeAlignment.ipy, and it looks for alignments with file names ending in _trim.fasta. The script uses RAxML for phylogenetic inference. The scripts should run within directory containing gene alignments
Requirements: IPython, RAxML (https://github.com/stamatak/standard-RAxML)
Current Versions: IPython 0.13.1, RAxML 8.0.6
Usage: GeneMLTrees.ipy
###mdsRFdistance.R
This script produces a plot of multidimensional scaling of Robinson-Foulds distances produced by RAxML.
Requirements: ggplot2, reshape2
Usage: mdsRFdistance.R [input file]
###eggNOGqueryFile.py
This script takes the first protein from each file in a directory of unaligned
fasta files and changes the protein ID to the name of the file. All protein
sequences are written to an output file that should be used as the query for
eggNOGblast.py.
Requirements: Biopython
Current Versions: Python 2.7.3, Biopython v 1.63
Usage: eggNOGqueryFile.py [directory of FASTA protein sequences]
###eggNOGblast.py
This script takes a file with fasta genes and uses NCBI BLAST+ to look for matches in the eggNOG BLAST database. It also uses eggNOG to assign functional categories to each fasta. Inputs are the directory where eggnog files are found and an input fasta.
Requirements: Biopython, NCBI BLAST+ (http://blast.ncbi.nlm.nih.gov/Blast.cgi?PAGE_TYPE=BlastDocs&DOC_TYPE=Download), eggNOG files (http://eggnog.embl.de/version_4.0.beta/downloads.v4.html), BLAST database created from eggNOG proteins
Current Versions: Python 2.7.3, Biopython 1.63, BLAST+ 2.2.18, eggNOG 4
Usage: eggNOGblast.py -f [input fasta file] -e [directory with eggNOG files]
###geneContentTree.py
This script uses the orthologous groups output by OrthoMCL to create a
distance matrix between strains. A neighbor joining tree is created from this
distance matrix.
Requirements: Biopython
Current Versions: Python 2.7.3, Biopython 1.64 (unreleased from https://github.com/biopython/biopython)
Usage: geneContentTree.py -g [OrthoMCL groups file]
###geneContentMatrix.py
This script uses the orthologous groups output by OrthoMCL to create a matrix of gene content for each genome in the analysis. Each row in the matrix is an orthologous group, and each column is a genome. The numbers correspond to the number of members of the group contained within each genome.
Current Versions: Python 2.7.3
Usage: geneContentMatrix.py -g [OrthoMCL groups file]
###compareCoreGenomes.py
This script used the orthologous groups output by OrthoMCL to create files describing the core genome and genes unique to the core genome of particular clades.
Format of clade file:
StrainA Clade1
StrainB Clade1
StrainC Clade2
Current Versions: Python 2.7.3
Usage: compareCoreGenomes.py [-n number] [-d] groups categories
-n number of genomes that can be missing a genome to be considered a core gene (default = 0)
-d allow duplicates of a gene within a genome