Metadata-Version: 2.1
Name: GMM-Demux
Version: 0.0.4
Summary: A multiplet removal tool for processing cell hashing data
Home-page: https://github.com/CHPGenetics/GMM-demux
Author: Hongyi Xin
Author-email: gohongyi@gmail.com
License: UNKNOWN
Description: # GMM-Demux 
        A Gaussian Mixture Model based software for processing cell hashing data.
        
        Blow shows an example classification result. Orange dots are multi-sample multiplets.
        
        <img src="GMM_simplified.png" alt="GMM-Demux example" width="600"/>
        
        
        ## Description
        GMM-Demux removes Multi-Sample-Multiplets (MSMs) in a cell hashing dataset and estimates the fraction of Same-Sample-Multiplets (SSMs) and singlets in the remaining dataset.
        
        ## Features
        * Remove cell-hashing-identifiable multiplets from the dataset.
        * Estimate the fraction of cell-hashing-unidentifiable multiplets in the remaining dataset (the RSSM value).
        
        ## Example Dataset
        * An example cell hashing data is provided in the *example_input* folder. It contains the per drop HTO count matrix of a 4-sample cell hashing library prep.
        
        # Authors
         Hongyi Xin, Qi Yan, Yale Jiang, Jiadi Luo, Carla Erb, Richard Duerr, Kong Chen* and Wei Chen*
        
        # Maintainer
        Hongyi Xin <xhongyi@pitt.edu>
        
        
        ## Requirement
        
        GMM-Demux requires python3 (>3.5).
        
        ## Install
        
        GMM-Demux can be directly installed from PyPi. Or it can be built and installed locally.
        
        * Install GMM-Demux from PyPi.
        ```bash
        pip3 install --user GMM_Demux
        ```
        If choose to install from PyPi, it is unnecessary to download GMM-Demux from github. However, we still recommend downloading the example dataset to try out GMM-Demux.
        
        * Install GMM-Demux locally using [setuptools](https://packaging.python.org/tutorials/installing-packages/) and pip3.
        ```bash
        cd <GMM-Demux dir>
        python3 setup.py sdist bdist_wheel
        pip3 install --user . 
        ```
        
        ## Usage
        
        Once installed, the github folder is no longer needed. Instead, GMM-Demux is directly accessible with the ```GMM-demux``` command.
        ```bash
        GMM-demux <cell_hashing_path> <HTO_names> <estimated_cell_num>
        ```
        MSM-free droplets are stored in folder *GMM_Demux_mtx* by default.
        
        ## Example Usage
        An example cell hashing data is provided in *example_input*. <HTO_names> can be obtained from the features.tsv file.
        ```bash
        GMM-demux example_input/outs/filtered_feature_bc_matrix HTO_1,HTO_2,HTO_3,HTO_4 35685
        ```
        
        <HTO_names> are obtained from the features.tsv file. An example is shown below.
        
        ![HTO names example](features.png)
        
        ## Optional Arguments
        * -h: show help information.
        * -f FULL, --full FULL  Generate the full classification report. Require a path argument.
        * -s SIMPLIFIED, --simplified SIMPLIFIED  Generate the simplified classification report. Require a path argument.
        * -o OUTPUT, --output OUTPUT  Specify the folder to store the result. Require a path argument.
        * -r REPORT, --report REPORT  Specify the file to store summary report. Require a file argument.
         
        ## Output Values
        * CellRanger MSM-free drops, in MTX format. Compatible with CellRanger 3.0.
        * Dataset summary. An example summary is shown below.
        ![Summary example](summary.png)
        
        ## Output Explanation
        * MSM denotes the percentage of identified and removed multiplets among all droplets.
        * SSM denotes the percentage of unidentifiable multiplets among all droplets.
        * RSSM denotes the percentage of multiplets among the output droplets (after removing identifiable multiplets). RSSM **measures the quality of the cell hashing dataset**.
        
        ## Online Cell Hashing Experiment Planner
        A GMM-Demux based online cell hashing experiment planner is publically accessible at [here](https://www.pitt.edu/~wec47/gmmdemux.html).
        
        [<img src="planner.png" alt="Online explanner example" width="800"/>](https://www.pitt.edu/~wec47/gmmdemux.html)
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3
Description-Content-Type: text/markdown
