corecomb 0.2.1

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Corecomb: create a XMFA file from Panaroo core gene alignments to detect recombination in core-genome using ClonalFrameML.

Installation

pip install corecomb

Quick start

If you are in Panaroo output directory, just run:

corerecomb 

Get help

$ corecomb --help

 Usage: corecomb [OPTIONS]

 Create XMFA file from ClonalFrameML input from Panaroo core-genome gene alignments

╭─ Options ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ --gene_al_dir    TEXT  Path to directory containing core-genome gene alignments [default: core_gene_alignments]                 │
│ --pan_fa         TEXT  Path to Panaroo pan_genome_reference.fa [default: pan_genome_reference.fa]                               │
│ --extension      TEXT  File extension of core-genome gene alignments [default: fas]                                             │
│ --outfile        TEXT  Path to output XMFA file [default: corecomb.xmfa]                                                        │
│ --help                 Show this message and exit.                                                                              │
╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯

Why

In theory, using the indivudal core-gene multiple sequence alignments from the core_gene_alignments directory of Panaroo, one could just run a sed command to concatenate these in a XMFA file.

sed -e '$s/$/\n=/' -s ../tests/data/aligned_gene_sequences_raw/*.fas > core_gene_alignment.xmfa

However, this approach suffers from 3 different issues:

• Sequence names need to be cleaned
• Ambiguous non N IUPAC characters need to be taken care of (CFML only accepts A,T,G,C,N,-)
• Genomes with missing genes will cause CFML to crash (core-genome defined at less 100%)

CoRecomb addresses all 3 of these issues. Additionally, CoRecomb uses the order of the genes defined in the pan_genome_reference.fa to re-order the genes in the XMFA file (which will be kept by CFML output core_gene_test_cfml.filtered.fasta).

Test it for yourself

poetry run pytest -vv

Test data can be found here tests/data

corecomb \
    --gene_al_dir tests/data/aligned_gene_sequences_raw \
    --pan_fa tests/data/pan_genome_reference.fa \
    --extension fas \
    --outfile corecomb.xmfa

Use the XMFA with ClonalFrameML

ClonalFrameML \
    input_tree.nwk \
    corecomb.xmfa \
    cfml_output_basename \
    -xmfa_file true \
    -show_progress true \
    -output_filtered true