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Author: luglilab

README.md

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+# Cytophenograph
+
+Identifies subpopulations in high-dimensional single-cell data. Cytophenograph is a computational pipeline that was developed to avoid the disadvantages of manual gating. The pipeline is developed using Python3, the clustering method adopted is a custom version of Phenograph (https://github.com/jacoblevine/PhenoGraph) where we insert a blocked seed. Besides Phenograph pipeline needs the following package installed: Pandas,Numpy,Sklearn for data parsing and exploring and openTSNE,Seaborn,Matplotlib for data visualization. This method is adaptative both in terms of dimensionality and sample size, making it suitable in a range of settings for which single-cell population structure is of interest, including other cancers or healthy tissues, and for use with other emerging single-cell technologies.
+
+## 1) Installation 
+
+Install Miniconda
+Miniconda is a Python distribution, package manager, and virtual environment solution. We recommend installing Miniconda with Python 3 (miniconda3), as many bioinformatics packages are now transitioning to Python 3. You can still install Python 2 software with miniconda3 by passing the python=2.7 flag when you create a new environment; otherwise the default Python version will be Python 3.
+
+Begin by downloading Miniconda and following the associated installation instructions.
+
+https://docs.conda.io/en/latest/miniconda.htm
+
+### Create your cytophenograph environment and install the dependences
+
+Test if miniconda3 is installed
+
+
+```python
+which conda
+```
+
+Clone our repository
+
+
+```python
+git clone https://github.com/luglilab/Cytophenograph
+```
+
+Create a new environment
+
+
+```python
+conda env create -n cytophenograph -f ./Cytophenograph/environment.yml 
+conda activate cytophenograph
+```
+
+Install Phenograph
+
+
+```python
+git clone https://github.com/luglilab/Phenograph_LugliLab
+```
+
+Move on Phenograph folder
+
+
+
+```python
+pip install -e Phenograph_LugliLab
+```
+
+```python
+pip install scipy==1.4.1 --use-feature=2020-resolver
+```
+
+```python
+conda install -c conda-forge umap-learn
+```
+
+
+```python
+cd ../Cytophenograph/
+python cytophenograph.py --help
+```
+
+
+Test Execution 
+```python
+mkdir output
+python cytophenograph.py -i ./CD8_Panel_II_channelvalues_GA/ -o ./output/ -k 300 -m ./marker.txt -n TestCytophenograph -t 10
+```