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Core-Genome Phylogenetic Trees

This script will allow you to build strain-level phylogenetic trees using consensus-alleles found in the core-genome.

The core-genome of a species is identified directly from the data by looking for genomic sites in the representative genome that have high coverage across multiple metagenomes.

Before running these scripts, you'll need to have run merge_midas.py snps read more.

Step 1. Call consensus alleles

Command usage:

Usage: call_consensus.py indir [options]

positional arguments:
  PATH                  path to output from `merge_midas.py snps` for one species
                        directory should be named according to a species_id and contains files 'snps_*.txt')

optional arguments:
  -h, --help            show this help message and exit
  --out PATH            path to output file

Sample filters (select subset of samples from INDIR):
  --sample_depth FLOAT  minimum average read depth per sample (0.0)
  --sample_cov FLOAT    fraction of reference sites covered by at least 1 read (0.0)
  --max_samples INT     maximum number of samples to process.
                        useful for quick tests (use all)
  --keep_samples STR    comma-separated list of samples to include
                        samples will still be subject to other filters
  --exclude_samples STR
                        comma-separated list of samples to exclude.
                        samples will still be subject to other filters

Site filters (select subset of genomic sites from INDIR):
  --site_list PATH      path to list of sites to include; other filters still apply
  --site_depth INT      minimum number of mapped reads per site (2)
  --site_prev FLOAT     site has at least <site_depth> coverage in at least <site_prev> proportion of samples (0.0)
                        a value of 1.0 will select sites that have sufficent coverage in all samples.
                        a value of 0.0 will select all sites, including those with low coverage in many samples
                        NAs recorded for included sites with less than <site_depth> in a sample
  --site_maf FLOAT      minimum average-minor-allele-frequency of site across samples (0.0)
                        setting this above zero (e.g. 0.01, 0.02, 0.05) will only retain variable sites
                        by default invariant sites are also retained.
  --site_ratio FLOAT    maximum ratio of site-depth to mean-genome-depth (None)
                        a value of 10 will filter genomic sites with 10x greater coverage than the genomic background
  --allele_support FLOAT
                        minimum fraction of reads supporting consensus allele (0.5)
  --locus_type {CDS,RNA,IGR}
                        use genomic sites that intersect: 'CDS': coding genes, 'RNA': rRNA and tRNA genes, 'IGS': intergenic regions
  --site_type {1D,2D,3D,4D}
                        if locus_type == 'CDS', use genomic sites with specified degeneracy: 4D indicates synonymous and 1D non-synonymous sites
  --max_sites INT       maximum number of sites to include in output (use all)
                        useful for quick tests

Examples

  1. Build multi-FASTA of core-genome sequences (recommended) -core-genome sites defined as >=5 reads in >=90% of samples -use only variable positions (>=1% minor allele frequency across samples) -only include samples with sufficient data (>=10x mean-depth, >=40% of sites with >=1 mapped read) -exclude sites with abnormal depth (>5x mean-depth or <1/5 mean-depth)

call_consensus.py /path/to/snps --out /path/to/seqs --site_maf 0.01 --site_depth 5 --site_prev 0.90 --sample_depth 10 --sample_cov 0.40 --site_ratio 5.0

  1. Build multi-FASTA using defaults call_consensus.py /path/to/snps --out /path/to/seqs

  2. Run a quick test call_consensus.py /path/to/snps --out /path/to/output --max_sites 10000

Step 2. Build phylogenetic tree

Now simply use your favorite tool to build the phylogenetic tree.

Example:
Download FastTree here
And, run: FastTree -gtr -nt < consensus.fa > consensus.tree

Step 3. Visualize tree

From a web-browser: iTOL
Or, from R: ape