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Project description

scevow

scevow: Excellent optimization of variant function mapping through weighted random walks at single-cell resolution

scevow: 通过单细胞分辨率下的加权随机游走对突变功能映射进行优化

1. 介绍

2. 上传

upload

test

py -m build
twine check dist/*
twine upload --repository testpypi dist/*

production

py -m build
twine check dist/*
twine upload dist/*

3. 使用

vim ~/.bashrc
export OMP_NUM_THREADS=1
export OPENBLAS_NUM_THREADS=1
source ~/.bashrc

test

pip3 install -r requirements.txt -i http://mirrors.aliyun.com/pypi/simple/ --trusted-host mirrors.aliyun.com
pip3 install scLift -i https://test.pypi.org/simple/

production

pip3 install scLift

Project details


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sclift-0.0.51.tar.gz (51.0 kB view details)

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scLift-0.0.51-py3-none-any.whl (62.7 kB view details)

Uploaded Python 3

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  • Download URL: sclift-0.0.51.tar.gz
  • Upload date:
  • Size: 51.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.10.12

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  • Download URL: scLift-0.0.51-py3-none-any.whl
  • Upload date:
  • Size: 62.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.10.12

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