DNBC4-test 1.0.7

DNBC4 scRNA QC

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^TM 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);"