GenomePainter

Paint genomes with taxonomic probabilities using k-mers from curated datasets

Table of contents

• Installation
• Usage
• Contributors
• License

Installation

Pre-compiled

Statically linked binaries for generic amd64 linux and ancillary Python scripts can be found under the GitHub releases page. GenomePainter can be run directly from these files (after downloading and extraction) without any required dependencies.

Brew

GenomePainter is available through the Brew and LinuxBrew package managers (thanks to @tseemann):

brew install brewsci/bio/genome-painter

Source

If you're feeling brave, you can attempt to compile the source. Autotools has been used for the build system so this process should be somewhat robust. First ensure you have the appropriate tools installed:

C++11 (gcc-4.9.0+, clang-4.9.0+, etc)
OpenMP 4.0+
GNU getopt
GNU automake
GNU autoconf
GNU autoconf-archive
GNU m4

Once these dependencies have been provisioned, compiling can be done by issuing:

./autogen.sh
./configure --prefix=$MY_INSTALL_PREFIX
make install -j4

It's also a good idea to run the included tests:

make check -j4

Usage

Data selection

The taxonomic groupings must be defined prior to using this tool. This typically involves acquisition of publicly available assemblies which are then curated. See fetching genomes for a bare bones method of quickly collecting all members (specified rank and below) of a taxonomic group. Curation is done manually by examining high-level, low-resolution phylogenetic relationships using mashtree.

k-mer counting

For each taxonomic group, the frequency of k-mers observed between assemblies is calculated. Currently only 32-mers can be used. Here the input data is a set of FASTA files representing genomes assemblies of a single taxa and the output is a single count file for that rank. So for each rank you must run:

./genomepainter_count_kmers --genome_fps [taxa_A_fasta_1, taxa_A_fasta_2, ...] --output_fp counts/taxa_A.tsv

This is straightforward to parallelise if the FASTA files are separated in some way (e.g. on a filesystem or via a predefined list):

parallel './genomepainter_count_kmers --genome_fps {}/*fasta --output_fp counts/{/}.tsv' ::: assemblies/*

Optionally genomepainter_count_kmers allows you to utilise additional threads by specifying --threads int , but this is only beneficial with thousands of genomes within a single rank.

Database generation

After k-mer counts have been done for all taxonomic groups, the final database can be generated:

./genomepainter_generate_database --count_fps counts/*tsv --output_fp database/my_database.bin

During database generation, the probability that a k-mer occurs in a species given a specific k-mer sequence is calculated. Extreme differences in sample sizes can cause apparent skewing of these probabilities. To mitigate these effects, you can specify a smooth factor α (see here for details) using --alpha. There are naturally many k-mers which cannot be used discriminate between taxa. Typically these k-mers are unwanted and can be filtered by adjusting the --threshold parameter. The value of this parameter relates to the absolute difference between the highest and second highest taxa probabilities for a given k-mer. If the difference is less than the --threshold value for these two probabilities, then the k-mer is excluded from the database.

Genome painting

To perform genome painting, all that is required is a database and one or more input FASTA assemblies:

./genomepainter_paint_genome --genome_fp [genome_1, genome_2, ...] --kmer_db_fp database/my_database.bin --output_dir output

During painting the k-mer with the highest probability for each position is selected. Painting a genome produces a single tab-delimited file for each input genome. The output file contains a set of all taxa probabilities for each position which has a hit in the database. See below for visualising the probabilities. If there are many genomes to paint, it is strongly recommended to use threads to reduce runtime. This is done by specifying --threads.

Visualising results

GenomePainter is distributed with a Python3 script to generate an interactive plots of results. This script requires the plot.ly Python library to be installed prior to use:

pip3 install --user plotly

The script accepts both uncompressed and gzipped painted genomes. To generate the interactive you can run:

./genomepainter_plot_painting.py --genome_painter_fp output/genome_1_painted.tsv.gz --output_fp plots/genome_1_painted.html

Output plots can be viewed using any modern web browers. An example plot can be found at https://paint.stephen.ac.

Contributors

• Ryan Wick
  • Offered considerable intellectual input for basis of method
  • Provided summary Python scripts (summarise_contigs.py and summarise_species.py)

License

GNU General Public License v3.0