mycorrhiza 0.0.18

Mycorrhiza population assignment tools.

Mycorrhiza

Combining phylogenetic networks and Random Forests for prediction of ancestry from multilocus genotype data.

Running an analysis from command line (OPTION 1)

1. Install Docker

   Instructions can be found here.

2. (On linux, optional) Give Docker root access.

3. Get the Mycorrhiza image.

   docker pull jgeofil/mycorrhiza:latest
   

4. Run an analysis.

   Example data can be found here.

   docker run -v [WORKING DIRECTORY]:/temp/ mycorrhiza crossvalidate -i /temp/[INPUT FILE] -o /temp
   

   For example, in a folder containing the input file gipsy.myc.

   docker run -v $PWD:/temp/ mycorrhiza crossvalidate -h
   docker run -v $PWD:/temp/ mycorrhiza crossvalidate -i /temp/gipsy.myc -o /temp
   

Running an analysis from command line (OPTION 2)

1. Make sure you have the latest version of Python 3.x

   python --version
   

2. Install pip

   https://pip.pypa.io/en/stable/installing/

3. Install Mycorrhiza

   pip3 install --upgrade mycorrhiza
   

4. Install SplitsTree

   Installation executables for SplitsTree4 can be found here.

5. Install matplotlib

   Instructions can be found here.

6. Run an analysis.

   crossvalidate -h
   crossvalidate -i gipsy.myc -o out/
   

   It may be necessary to add to the PATH

   export PATH=$PATH:$HOME/.local/bin
   

Running an analysis in a script

Installing Mycorrhiza with pip

1. Make sure you have the latest version of Python 3.x

   python --version
   

2. Install pip

   https://pip.pypa.io/en/stable/installing/

3. Install Mycorrhiza

   pip3 install --upgrade mycorrhiza
   

4. Install SplitsTree

   Installation executables for SplitsTree4 can be found here.

5. Install matplotlib

   Instructions can be found here.

Running an analysis in a script

1. Import the necessary modules.

   from mycorrhiza.dataset import Myco
   from mycorrhiza.analysis import CrossValidate
   from mycorrhiza.plotting.plotting import mixture_plot
   

2. (Optional) By default Mycorrhiza will look for SplitStree in your PATH. I you wish to specify a different path for the SplitsTree executable you can do so in the settings module.

   from mycorrhiza.settings import const
   const['__SPLITSTREE_PATH__'] = 'SplitsTree'
   

3. Load some data. Here data is loaded in the Mycorrhiza format from the Gipsy moth sample data file. Example data can be found here.

   myco = Myco(file_path='data/gipsy.myc')
   myco.load()
   

4. Run an analysis. Here a simple 5-fold cross-validation analysis is executed on all available loci, without partitioning.

   cv = CrossValidate(dataset=myco, out_path='data/')
   cv.run(n_partitions=1, n_loci=0, n_splits=5, n_estimators=60, n_cores=1)
   

5. Plot the results.

   mixture_plot(cv)
   

Documentation

https://jgeofil.github.io/mycorrhiza/

File formats

Myco

Diploid genotypes occupy 2 rows (the sample identifier must be identical).

Column(s)	Content	Type
1	Sample identifier	string
2	Population	string or integer
3	Learning flag	{0,1}
4 to M+3	Loci	{A, T, G, C, N}

STRUCTURE

Diploid genotypes occupy 2 rows (the sample identifier must be identical).

Column(s)	Content	Type
1	Sample identifier	string
2	Population	integer
3	Learning flag	{0,1}
4 to O+3	Optional (Ignored)
O+3 to M+O+3	Loci	integer or -9