KnowEnG's Clustering Evaluation Pipeline

This is the Knowledge Engine for Genomics (KnowEnG), an NIH BD2K Center of Excellence, Clustering Evaluation Pipeline.

This pipeline evaluates the clustering result of KnowEnG's Samples Clustering Pipeline.

There are two evaluation methods:

Method	Trait Type
one-way ANOVA(f_oneway)	Continuous
one-way chi square test(chisquare)	Categorical

---

How to run this pipeline with Our data

---

###1. Clone the Clustering_Evaluation Repo

 git clone https://github.com/KnowEnG-Research/Clustering_Evaluation.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 Clustering_Evaluation

cd Clustering_Evaluation

###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 clustering evaluation option:

• Run clustering evaluation
  

make run_cluster_eval

---

How to run this pipeline with Your data

---

Follow steps 1-3 above then do the following:

* Create your run directory

mkdir run_directory

* Change directory to the run_directory

cd run_directory

* Create your results directory

mkdir results_directory

* Create run_paramters file (YAML Format)

Look for examples of run_parameters in the Clustering_Evaluation/data/run_files template_run_parameters.yml

* Run the Clustering Evaluation Pipeline:

• Update PYTHONPATH enviroment variable

export PYTHONPATH='./src':$PYTHONPATH    

• Run

python3 ../src/clustering_eval.py -run_directory ./ -run_file BENCHMARK_1_cluster_eval.yml

---

Description of "run_parameters" file

---

Key	Value	Comments
phenotype_data_full_path	directory+phenotype_data_name	Path and file name of user supplied phenotype data
cluster_mapping_full_path	directory+cluster_mapping_data_name	Path and file name of sample labels by cluster
results_directory	directory	Directory to save the output files
threshold	10	Maximum number of traits for categorical phenotype

phenotype_data_name = UCEC_phenotype.txt
cluster_mapping_data_name = samples_label_by_cluster.tsv

---

Description of Output files saved in results directory

---

• The clustering evaluation output file has the name clustering_evaluation_result_{timestamp}.tsv.
  

	Measure	Trait_length_after_dropna	Sample_number_after_dropna	chi/fval	pval
sample 1	f_oneway	int(more than threshold)	int	float	float
...	...	...	...	...	...
sample m	chisquare	int(less than threshold)	int	float	float