SCYN 1.0.3

SCYN: Single cell CNV profiling method using dynamic programming efficiently and effectively

SCYN: Single cell CNV profiling method usingdynamic programming efficiently andeffectively

SCYN: Single cell CNV profiling method usingdynamic programming efficiently andeffectively

Pre-requirements

• python3
• numpy>=1.16.1
• pandas>=0.23.4,<0.24
• tasklogger>=0.4.0
• scipy>=1.3.0
• SCOPE

install requirements

pip install -r requirements.txt

To install R package SCOPE, please refer to the README of 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:

pip install scyn

Installation from Github

To clone the repository and install manually, run the following from a terminal:

git clone https://github.com/xikanfeng2/SCYN.git
cd SCYN
python setup.py install

Usage

Quick start

The following code runs SCYN.

In command line:

usage: python run-scyn.py [-h] [options] -i input_bams_dir

SCYN: Single cell CNV profiling method using dynamic programming efficiently
and effectively

required arguments:
  -i, --indir   <str> the input bams directory (default: None)

optional arguments:
  -o, --outdir  <str> the output directory (default: ./)
  --seq           <str> the reads type: single-end or paired-end. (default:
                    single-end)
  --bin_len       <int> the bin length, default is 500K. (default: 500)
  --ref           <str> the reference genome version: hg19 or hg38.
                    (default: hg19)
  --reg           <str> the regular expression to match all BAM files in
                    your input directory. For example, ".bam" will match all
                    BAM files ended with '.bam'. (default: *.bam)
  --mapq          <int> the mapping quality cutoff when calculating the
                    reads coverage. (default: 40)
  --K             <int> the changepoints number for each chromosome.
                    (default: 10)
  --verbose       <int> If > 0, print log messages. (default: 1)
  -h, --help

In 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

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 [e-mail].