Metadata-Version: 2.1
Name: DNBC4-test
Version: 1.0.7
Summary: DNBC4 scRNA QC
Home-page: https://github.com/MGI-tech-bioinformatics/DNBelab_C_Series_HT_scRNA-analysis-software
Author: lishuangshuang3
Author-email: lishuangshuang3@mgi-tech.com
License: MIT
Description: # DNBC4tools
        An open source and flexible pipeline to analysis high-throughput DNBelab C Series single-cell RNA datasets
        ## Introduction
        - **Propose**
          - An open source and flexible pipeline to analyze DNBelab C Series<sup>TM</sup> single-cell RNA datasets. 
        - **Language**
          - Python3 and R scripts.
        - **Hardware/Software requirements** 
          - x86-64 compatible processors.
          - require at least 50GB of RAM and 4 CPU. 
          - centos 7.x 64-bit operating system (Linux kernel 3.10.0, compatible with higher software and hardware configuration). 
        
        ## Installation
        installation manual
        
        ### Install miniconda and creat DNBC4tools environment
        - Git clone
        ```
        git clone https://github.com/lishuangshuang0616/DNBC4tools.git
        ```
        - Install miniconda3
        ```
        wget -nv https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
        sh Miniconda3-latest-Linux-x86_64.sh -b -p $PATH
        ```
        - Creat DNBC4tools environment
        ```
        cd DNBC4tools
        source /miniconda3/bin/activate
        conda env create -f DNBC4tools_conda.yaml -n DNBC4tools
        ```
        - Install R package that cannot be installed using conda
        ```
        conda activate DNBC4tools
        Rscript -e "devtools::install_github(c('chris-mcginnis-ucsf/DoubletFinder','ggjlab/scHCL','ggjlab/scMCA'),force = TRUE);"
        ```
Platform: Linux
Requires-Python: >=3.7.*
Description-Content-Type: text/markdown
