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Non-redundant pangenome assemblies from multiple genomes or bins

Project description

SuperPang: non-redundant pangenome assemblies from multiple genomes or bins

Installation

Requires graph-tool, mOTUlizer v0.2.4, minimap2 and mappy. The easiest way to get it running is using conda.

# Install into a new conda environment
conda create -n SuperPang -c conda-forge -c bioconda -c fpusan superpang
# Check that it works for you!
conda activate SuperPang
test-SuperPang.py

Usage

SuperPang.py --fasta <genome1.fasta> <genome2.fasta> <genomeN.fasta> --checkm <check_results> --output-dir <output_directory>

Input files and choice of parameters

  • The input genomes can be genomes from isolates, MAGs (Metagenome-Assembled Genomes) or SAGs (Single-cell Assembled Genomes).
  • The input genomes can have different qualities, for normal usage we recommend that you provide completeness estimates for each input genome through the -q/--checkm parameter.
  • If you are certain that all your input genomes are complete, you can use the --assume-complete flag or manually tweak the -a/--genome-assignment-threshold and -x/--default-completeness parameters instead of providing a file with completeness estimates.
  • The default parameter values in SuperPang assume that all of the input genomes come from the same species (ANI>=0.95). This can be controlled by changing the values of the -i/--identity_threshold and -b/--bubble-identity-threshold to the expected ANI. However SuperPang has currently only been tested in species-level clusters.

Arguments

  • -f/--fasta: Input fasta files with the sequences for each bin/genome
  • -q/--checkm: CheckM output for the bins. This can be the STDOUT of running checkm on all the fasta files passed in --fasta, or a tab-delimited file in the form genome1 percent_completeness. If empty, completeness will be estimated by mOTUpan but this may lead to wrong estimations for very incomplete genomes.
  • -i/--identity_threshold: Identity threshold (fraction) to initiate correction with minimap2. Values of 1 or higher will skip the correction step entirely. Default 0.95.
  • -m/--mismatch-size-threshold: Maximum contiguous mismatch size that will be corrected. Default 100.
  • -g/--indel-size-threshold: Maximum contiguous indel size that will be corrected. Default 100.
  • -r/--correction-repeats: Maximum iterations for sequence correction. Default 20.
  • -n/--correction-repeats-min: Minimum iterations for sequence correction. Default 5.
  • -k/--ksize: Kmer-size. Default 301.
  • -l/--minlen: Scaffold length cutoff. Default 0 (no cutoff).
  • -c/--mincov: Scaffold coverage cutoff. Default 0 (no cutoff).
  • -b/--bubble-identity-threshold: Minimum identity (matches / length) required to remove a bubble in the sequence graph. Default 0.95.
  • -a/--genome-assignment-threshold. Fraction of shared kmers required to assign a contig to an input genome (0 means a single shared kmer is enough). Default 0.5.
  • -x/--default-completeness: Default genome completeness to assume if a CheckM output is not provided with --checkm. Default 50.
  • -t/--threads: Number of processors to use. Default 1.
  • -o/--output: Output directory. Default output.
  • --assume-complete: Assume that the input genomes are complete (--genome-assignment-threshold 0.95, --default-completeness 99).
  • --minimap2-path: Path to the minimap2 executable. Default minimap2.
  • --keep-intermediate: Keep intermediate files.
  • --verbose-mOTUpan: Print out mOTUpan logs.

Output

  • assembly.fasta: contigs.
  • assembly.info: core/auxiliary and path information for each contig.
  • nodes.fasta: non-branching paths.
  • core.fasta: non-branching paths deemed to belong to the core genome of the species by mOTUpan.
  • auxiliary.fasta: non-branching paths deemed to belong to the auxiliary genome of the species.
  • graph.fastg: assembly graph in a format compatible with bandage.
  • node2origins.tsv: tab-separated file with the assembly nodes, and a comma-separated list of the input genome in which that node was deemed present.
  • params.tsv: parameters used in the run.

About

SuperPang is developed by Fernando Puente-Sánchez (Sveriges lantsbruksuniversitet). Feel free to open an issue or reach out for support fernando.puente.sanchez@slu.se.

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