Metadata-Version: 1.2
Name: scalex
Version: 0.0.2
Summary: Single-cell Analysis via Latent feature Extraction universally
Home-page: https://github.com/jsxlei/scalex
Author: Lei Xiong
Author-email: jsxlei@gmail.com
License: MIT
Description: # SCALEX: Single-cell Analysis via latent Feature Extraction Universally 
        
        ## Installation  	
        #### install from PyPI
        
            pip install scalex
            
        #### install from GitHub
        
        	git clone git://github.com/jsxlei/scalex.git
        	cd scalex
        	python setup.py install
            
        scalex is implemented in [Pytorch](https://pytorch.org/) framework.  
        Running scalex on CUDA is recommended if available.   
        Installation only requires a few minutes.  
        
        ## Quick Start
        
            scalex.py --name name --data_list data1 data2 ... datan --batch_categories batch1 batch2 ... batch n 
            
            data_list: different batches of dataset, single
            batch_categories: is optional
            
        
        #### Output
        Output will be saved in the output folder including:
        * **checkpoint**:  saved model to reproduce results cooperated with option --checkpoint or -c
        * **adata.h5ad**:  preprocessed data and results including, latent, clustering and imputation
        * **umap.png**:  UMAP visualization of latent representations of cells 
        * **log.txt**:  log file of training process
        
             
        #### Useful options  
        * save results in a specific folder: [-o] or [--outdir] 
        * filter rare genes, default 3: [--min_cell]
        * filter low quality cells, default 600: [--min_gene]  
        * select the number of highly variable genes, keep all genes with -1, default 2000: [--n_top_genes]
        	
            
        #### Help
        Look for more usage of scalex
        
        	scalex.py --help 
            
            
        #### Tutorial
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.7
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX :: Linux
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >3.6.0
