KnowEnG's Phenotype Prediction Pipeline

This is the Knowledge Regression for Genomics (KnowEnG), an NIH BD2K Center of Excellence, Phenotype Prediction Pipeline that will be used to infer an 'omic'-drug association.

The user will need to do of the following in order for the system to learn how to predict the phenotype through regression:

• User must submit an ‘omic’ spreadsheet with samples as columns and genes as rows.
• User will also need to submit a phenotype value for each sample.

This will allow one to:

• Identify the best drug for a patient.

Given an omic spreadsheet of a collection of genes as well as the supplied phenotype value, the user will need to choose one of these options:

Options	Method	Parameters
Elastic Net	Elastic	elastic_net
Lasso	Lasso	Lasso

---

How to run this pipeline with our data

---

1. Clone the Phenotype_Prediction_Pipeline

 git clone https://github.com/KnowEnG/Phenotype_Prediction_Pipeline.git

2. Install the following (Ubuntu or Linux)

apt-get install -y python3-pip
apt-get install -y libblas-dev liblapack-dev libatlas-base-dev gfortran
pip3 install numpy==1.11.1
pip3 install pandas==0.18.1
pip3 install scipy==0.18.0
pip3 install scikit-learn==0.17.1
apt-get install -y libfreetype6-dev libxft-dev
pip3 install matplotlib=1.4.2
pip3 install pyyaml
pip3 install knpackage

3. Change directory to Phenotype_Prediction_Pipeline

cd Phenotype_Prediction_Pipeline

4. Change directory to test

cd test

5. Create a local directory "run_dir" and place all the run files in it

make env_setup

6. Select and run a phenotype prediction option:

• Run Elastic Net pipeline
  

make run_elastic_net

• Run Lasso pipeline
  

make run_lasso

Follow steps 1-3 above then do the following:

* Create your results directory

mkdir results_directory

* Create run_parameters file (YAML Format)

Look for examples of run_parameters in:

Phenotype_Prediction_Pipeline/data/run_files BENCHMARK_2_ElasticNet.yml

Phenotype_Prediction_Pipeline/data/run_files BENCHMARK_1_PPP_Lasso.yml

* Run

Using Elastic net

python3 ../src/phenotype.prediction.py -run_directory ./run_dir -run_file BENCHMARK_2_ElasticNet.yml

Using Lasso

python3 ../src/phenotype.prediction.py -run_directory ./run_dir -run_file BENCHMARK_1_PPP_Lasso.yml

---

Description of "run_parameters" file

---

Key	Value	Comments
Elastic Net	Method	http://scikit-learn.org/stable/modules/linear_model.html#elastic-net
Lasso	Method	http://scikit-learn.org/stable/modules/linear_model.html#lasso
results_directory	Directory	Directory to save the output files

spreadsheet_name = features_train_clean.df
response_name = response_train_clean.df
test_spreadsheet_name = features_test_clean.df

---

Description of Output files are saved in results directory

---

Gene Name	Prediction
User Gene 1	Float
...	...
User Gene n	Float