Metadata-Version: 2.1
Name: DNBC4dev
Version: 1.0.7
Summary: DNBC4 scRNA QC
Home-page: https://github.com/lishuangshuang0616/DNBC4dev
Author: lishuangshuang3
Author-email: lishuangshuang3@mgi-tech.com
License: MIT
Platform: Linux
Requires-Python: >=3.8.*
Description-Content-Type: text/markdown
Requires-Dist: plotly (==4.14.3)
Requires-Dist: matplotlib (==3.5.1)
Requires-Dist: multiprocess (==0.70.12.2)
Requires-Dist: plotnine (==0.8.0)
Requires-Dist: scipy (==1.8.0)
Requires-Dist: statsmodels (==0.13.2)
Requires-Dist: datatable (==0.11.1)
Requires-Dist: numpy (==1.22.2)
Requires-Dist: pandas (==1.4.1)

# DNBC4dev
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 DNBC4dev environment
- Creat DNBC4dev environment
```
cd DNBC4dev
source /miniconda3/bin/activate
conda env create -f DNBC4dev.yaml -n DNBC4dev
```
- Install R package that cannot be installed using conda
```
conda activate DNBC4dev
Rscript -e "devtools::install_github(c('chris-mcginnis-ucsf/DoubletFinder','ggjlab/scHCL','ggjlab/scMCA'),force = TRUE);"
```


