mycorrhiza-algorithm

KO | EN

gitlite — search

#python #hacktoberfest #react #android #machine-learning #deep-learning #linux #macos #awesome #kubernetes #vue #pytorch #security #open-source

mycorrhiza-algorithm

(★ 8)

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

mycorrhiza-algorithm 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# Mycorrhiza algorithm
*Published in -Mycorrhiza: Combining phylogenetic networks and Random Forests for prediction of ancestry from multilocus genotype data*

[![ReadMe Card](https://github-readme-stats.vercel.app/api/pin/?username=jgeofil&repo=mycorrhiza-article-source)](https://github.com/jgeofil/mycorrhiza-article-source)

## Installing Mycorrhiza on Ubuntu 16.04

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

```bash
    python3 --version
    ```

2. Install pip3, Java and the tkinter library

```bash
    sudo apt-get install python3-pip python3-tk default-jre
    ```

3. Install Mycorrhiza

```bash
    pip3 install --upgrade mycorrhiza
    ```

4. Install SplitsTree
    
    Follow the instructions in the GUI installer, leaving all settings to default.
    ```bash
    wget http://ab.inf.uni-tuebingen.de/data/software/splitstree4/download/splitstree4_unix_4_14_6.sh
    chmod +x splitstree4_unix_4_14_6.sh
    ./splitstree4_unix_4_14_6.sh
    ```

If the link above is not available - find the most recent version of the SplitsTree: 
    http://ab.inf.uni-tuebingen.de/data/software/splitstree4/download

## Installing Mycorrhiza on Mac OS X Sierra 10.12

1. If you don't already have the package manager HomeBrew, install it before proceeding.

```bash
    ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
    
    ```
    
2. Install Python 3.x

```bash
    brew install python
    ```

3. Install Mycorrhiza

```bash
    sudo -H pip3 install --upgrade mycorrhiza
    ```
    
4. Install SplitsTree

The package can be found [here](http://ab.inf.uni-tuebingen.de/data/software/splitstree4/download/splitstree4_macos_4_14_6.dmg).
    Follow the installer instructions, leaving all settings to default.

If the link above is not available - find the most recent version of the SplitsTree: 
    http://ab.inf.uni-tuebingen.de/data/software/splitstree4/download

## Running an analysis from command line

1. Run an analysis.

Run a 5-fold crossvalidated analysis.
    ```bash
    crossvalidate -i gipsy.myc -o out/ -s 5
    ```

Run a analysis with a training set and a prediction set. Samples with a learing flag = 1 will 
    be used for training and predictions will be made on samples with a learning flag = 0.
    ```bash
    supervised -i gipsy.myc -o out/
    ```

To see all available parameters:
    ```bash
    crossvalidate -h
    ```

## Running an analysis in a script

1. Import the necessary modules.
    
    ```python
    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 home folder. 
I you wish to specify a different path for the SplitsTree executable you can do so in the settings module.

```python
    from mycorrhiza.settings import const
    const['__SPLITSTREE_PATH__'] = '~/splitstree4/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](https://github.com/jgeofil/mycorrhiza/tree/master/examples/data).

```python
    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.

```python
    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.

```python
    mixture_plot(cv)
    ```
    
## Documentation

[https://jgeofil.github.io/mycorrhiza/](https://jgeofil.github.io/mycorrhiza/)

## File formats
For microsatellite loci set the is_str flag to True.

```python
    data = Myco(file_path='data/myco.myc', is_str=True)
    data = Structure(file_path='data/myco.str', is_str=True)
    ```

### 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  | SNP Loci	        | {A, T, G, C, N}            |
| 4 to M+3  | STR Loci	        | any or 000                 |

### 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  | SNP Loci	        | integer or -9              |
| O+3 to M+O+3  | STR Loci	        | any or -9                  |

mycorrhiza-algorithm

mycorrhiza-algorithm 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

mycorrhiza-algorithm

mycorrhiza-algorithm 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

Download README