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Reproducible analysis on the genome/phenome of four bacterial datasets

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ductape_data

This repository is intended to make the analysis of DuctApe on the test cases fully reproducible. All the necessary input data are provided, as well as a detailed script to run each command used in the analysis.

Requirements

  • DuctApe v0.16.4 or later

  • OrthoMCL

  • InParanoid/MultiParanoid

Howto

Choose the test set from the directories provided.

Once inside a directory, just type from the command line:

./runDuctApe

To perform the ortholog prediction benchmark (please note that the BLOSUM80 matrix has been used):

  • The DuctApe orthologs are calculated as part of the runDuctApe script (file pangenome_category.tsv)

  • InParanoid/MultiParanoid:

    • Compute the pairwise comparisons with the parapy script (orthologs folder)

    • Run MultiParanoid

    • Run the mp2tsv script (orthologs folder) to obtain the pangenome_category.tsv

  • OrthoMCL:

    • Follow the OrthoMCL tutorial and obtain the groups.txt file; keep the compliantFasta directory

    • Run the omcl2tsv script (orthologs folder) to obtain the pangenome_category.tsv

The pangenome_category.tsv files can be easily compared using standard command line tools; for instance:

cat pangenome_category.tsv | grep -c core

Will output the number of core genome orthologous groups that are present.

Comparison with published data

The acinetobacter and zmobilis folders contain data already published; the publications are the following:

  • acinetobacter: Peleg, Anton Y., et al. "The success of acinetobacter species; genetic, metabolic and virulence attributes." PloS one 7.10 (2012): e46984.

  • zmobilis: Bochner, Barry, et al. "Phenotype microarray profiling of Zymomonas mobilis ZM4." Applied biochemistry and biotechnology 161.1-8 (2010): 116-123.

Acknowledgements

  • Dr. Bosi for the parapy script
  • Dr. Bochner and Dr. Ziman for the Z. mobilis PM data
  • Prof. Peleg and Dr. Dijkshoorn for the Acinetobacter PM data

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Reproducible analysis on the genome/phenome of four bacterial datasets

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