1. Ke Yuan
  2. BitPhylogeny

Overview

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Overview

This README file discusses the code associated with the manuscript:

Ke Yuan, Thomas Sakoparnig, Florian Markowetz and Niko Beerenwinkel. (2015) BitPhylogeny: a probabilistic framework for reconstructing intra-tumor phylogenies. Genome Biology. Accepted

The Python code is based on the implementation from Ryan Prescott Adams, Zoubin Ghahramani and Michael I. Jordan. (2010) Tree-Structured Stick Breaking for Hierarchical Data. NIPS. http://hips.seas.harvard.edu/files/tssb.tgz


License

BitPhylogeny is licensed under the GPL v3, see the LICENSE.txt file for details.


Dependencies and tested versions

  1. Python 2.7.6:

  2. R 3.2.0:

    • rPython 0.0-6
    • mcclust 1.0
    • e1071 1.6-7
    • igraph 0.7.1
    • gplots 2.17.0
    • riverplot 0.5
    • plyr 1.8.2.

Installation

Clone the BitPhylogeny repository:

git clone git@bitbucket.org:ke_yuan/bitphylogeny.git 
cd bitphylogeny

Install the BitPhylogeny python package:

cd python
sudo python setup.py install

Install the R package:

cd ../R
R CMD INSTALL bitphylogenyR_0.99.tar.gz

Useage

We've provided a sample data file 'sample_data.csv' in the python folder. To run the sample file, execute the following code.

BitPhylogeny analyse 'sample_data.csv' 'output' -true_label -n 200 -b 10 -t 5 -mode "methylation" -seed 1234 
'sample_data.csv': the data file. Please make sure rows represent data points, colums represent dimension 
'output': the output folder where the MCMC traces and tree scripts are stored.
-true_label: data file contains true labels as the last column.
-n: number of mcmc samples in total 
-b: number of burn-in samples
-t: thin number (a current requirement is (number of mcmc samples / thin) > 5)
-mode: "methylation" or "mutation"
-seed: default 1234
-row_names: the first colum of the data file is row names 

The output folder contains the mcmc-traces and treescripts.

For post processing, please use the accompanying R package. Tutorials of the R package are stored in doc/ directory