implementation for the Precision Lasso
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models
utility
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BasicExample.ipynb
README.md
requirements.txt
runPL.py
setup.py

README.md

the Precision Lasso

Implementation of the Precision Lasso in this paper:

''Wang H, Lengerich BJ, Aragam B, Xing EP. Precision Lasso: Accounting for Correlations and Linear Dependencies in High-Dimensional Genomic Data. Bioinformatics. 2017''

Introduction

the Precision Lasso is a Lasso variant that is showed to work better compared to other Lasso variants in terms of variable selection when there are correlated and linearly dependent variables existing.

File Structure:

  • models/ main method for the Precision Lasso
  • utility/ other helper files
  • runPL.py main entry point of using the Precision Lasso to work with your own data

An Example Command:

python runPL.py -t csv -n data/toy

Data Support

  • Precision Lasso currently supports CSV and binary PLINK files.
  • Extensions to other data format can be easily implemented through FileReader in utility/dataLoadear. Feel free to contact us for the support of other data format.

Installation

You will need to have numpy and scipy installed on your current system. You can install precision lasso using pip by doing the following

   pip install git+https://github.com/HaohanWang/thePrecisionLasso

You can also clone the repository and do a manual install.

   git clone https://github.com/HaohanWang/thePrecisionLasso
   python setup.py install

Software with GUI

Software with GUI will be avaliable through GenAMap

Python Users

Proficient python users can directly call the Precision Lasso with python code, see the example here

Contact

Haohan Wang