[This project is in active development and not currently recommended for public use.]
CompareM is a comparative genomics toolbox. It provides statistics across groups of genomes (e.g., amino acid identity; core, dispensible, and unique gene sets) and for individual genomes (e.g., GC content, coding density, codon usage). Emphasis has been placed on providing parallelized implementations in order to allow scalability to thousands of genomes. The functionality currently planned is:
Comparative genomic statistics:
- average amino acid identity (AAI) between genomes
- average nucleotide identity (ANI) between genomes
- core, dispensible, and unique gene sets
Single genome statistics:
- GC content
- coding density
- codon and amino acid usage
- automatic identification of translation table
- N50; maximum and mean scaffold/contig size; no. of scaffolds/contigs
Genomic usage patterns:
- codon usage
- amino acid usage
- kmer usage for k <= 8 (e.g., tetranucleotide)
- stop codon usage
- Visualization of usage patterns with PCA plots and hierarchical clustering dendrograms
A number of auxillary tools are also provides which are often helpful within comparative genomic studies:
- identification of homologous genes followed by alignment and tree inference
- back-translation of amino acid alignments to nucleotides
The simplest way to install this package is through pip:
sudo pip install comparem
This package requires numpy to be installed and makes use of the follow bioinformatic packages:
- prodigal: Hyatt D, Locascio PF, Hauser LJ, Uberbacher EC. 2012. Gene and translation initiation site prediction in metagenomic sequences. Bioinformatics 28: 2223-2230.
- blast+: Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J, Bealer K, Madden TL. 2009. BLAST+: architecture and applications. BMC Bioinformatics 10:421: doi: 10.1186/1471-2105-10-421.
- fasttree: Price MN, Dehal PS, Arkin AP. 2010. FastTree 2: approximately maximum-likelihood trees for large alignments. PLoS ONE, 5:e9490. doi:10.1371/journal.pone.0009490.
- muscle: Edgar RC. 2004. MUSCLE: multiple sequence alignment with high accuracy and throughput. Nucleic Acids Research 32: 1792-1797. doi: 10.1093/nar/gkh340.
- diamond Buchfink B, Xie C, Huson DH. 2015. Fast and sensitive protein alignment using DIAMOND. Nature Methods 12: 59–60 doi:10.1038/nmeth.3176.
If you find this package useful, please cite this git repository (https://github.com/dparks1134/CompareM)
Copyright © 2014 Donovan Parks. See LICENSE for further details.