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A toolbox for improving population genomes.

Project description

[This project is in active development and not currently recommended for public use.]

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RefineM is a set of tools for improving population genomes. It provides methods designed to improve the completeness of a genome along with methods for identifying and removing contamination. RefineM comprises only part of a full genome QC pipeline and should be used in conjunction with existing QC tools such as CheckM. The functionality currently planned is:

Improve completeness:

  • identify contigs with similarity to specific reference genome(s)

  • identify contigs with compatible GC, coverage, and tetranucleotide signatures

  • indetify partial population genomes which should be merged together (requires CheckM)

Reducing contamination:

  • taxonomically classify contigs within a genome in order to identify outliers

  • identify contigs with divergent GC content, coverage, or tetranucleotide signatures

  • identify contigs with a coding density suggestive of a Eukaryotic origin

Install

The simplest way to install this package is through pip: > sudo pip install refinem

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.

  • 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.

  • krona Ondov BD, Bergman NH, and Phillippy AM. 2011. Interactive metagenomic visualization in a Web browser. BMC Bioinformatics 12: 385.

Cite

If you find this package useful, please cite this git repository (https://github.com/dparks1134/refinem)

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refinem-0.0.15.tar.gz (4.2 MB view hashes)

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