Metadata-Version: 2.1
Name: SCYN
Version: 1.0.1
Summary: SCYN: a local optimal single cell CNV profiling method using dynamic programming
Home-page: https://github.com/xikanfeng2/SCYN
Author: Xikang Feng
Author-email: xikanfeng2@gmail.com
License: UNKNOWN
Description: # SCYN: a local optimal single cell CNV profiling method using dynamic programming
        
        SCYN: a local optimal single cell CNV profiling method using dynamic programming
        
        ## Pre-requirements
        * python3
        * numpy>=1.16.1
        * pandas>=0.23.4,<0.24
        * tasklogger>=0.4.0
        * scipy>=1.3.0
        * [SCOPE](https://github.com/rujinwang/SCOPE)
        
        
        ### install requirements
        ```Bash
        pip install -r requirements.txt
        ```
        To install R package SCOPE, please refer to the README of [SCOPE](https://github.com/rujinwang/SCOPE). SCYN integrates the SCOPE to get the cell-by-bin reads depth matrix and perform the normalization. SCYN mainly focuses on finding the optimal CNV segmentation profiling using dynamic programming.
        
        ## Installation
        
        ### Installation with pip
        To install with pip, run the following from a terminal:
        ```Bash
        pip install scyn
        ```
        
        ### Installation from Github
        To clone the repository and install manually, run the following from a terminal:
        ```Bash
        git clone https://github.com/xikanfeng2/SCYN.git
        cd SCYN
        python setup.py install
        ```
        
        ## Usage
        
        ### Quick start
        The following code runs SCYN.
        
        ```Python
        import scyn
        
        # create SCYN object
        scyn_operator = scyn.SCYN()
        
        # call cnv
        # bam_dir is the input bam directory and output_dir is the output directory
        scyn_operator.call(bam_dir, output_dir)
        
        # store cnv matrix to a csv file
        scyn_operator.cnv.to_csv('your file name')
        ```
        
        ### Parameters
        ```Python
        SCYN(seq='single-end', bin_len=500, ref='hg19', reg='*.bam', mapq=40, K=10, verbose=1)
        ```
        Parameters
        
        * seq : string, optional, default: single-end
            The reads type: single-end or paired-end
        
        * bin_len : int, optional, default: 500
            The bin length, default is 500K
        
        * ref : string, optional, default: hg19
            The reference genome version: hg19 or hg38
        
        * reg : string, optional, default: *.bam
            The regular expression to match all BAM files in your input directory.
            For example, "*.bam" will match all BAM files ended with '.bam'
        
        * mapq : int, optional, default: 40
            The mapping quality cutoff when calculating the reads coverage
        
        * K : int, optional, default: 10
            The predifined change points number for all chromosomes
        
        
        * verbose : `int` or `boolean`, optional, default: 1
        
            If `True` or `> 0`, print status messages
        
        ## Cite us
        
        ## Help
        If you have any questions or require assistance using SCYN, please contact us with xikanfeng2@gmail.com.
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
