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2023-07-09-【记录】安装生信的代码编写环境.md

2023-07-09-【记录】安装生信的代码编写环境.md 10 KB
Історія Запис

title: 【记录】安装生信的代码编写环境 urlname: -ji-lu--an-zhuang-sheng-xin-de-dai-ma-bian-xie-huan-jing date: 2023-07-09 20:01:33

tags: ['生信', 'docker', 'vscode', 'rstudio', 'jupyter']

安装 vscode-web

  • 安装好 docker

  • QUIC 转 SOCKS5

    mkdir -p ~/app/vscode && cd ~/app/vscode && nano docker-compose.yml
sudo docker-compose up -d && sudo docker-compose logs

    version: "2.1"
services:
code-server:
image: linuxserver/code-server:latest
container_name: code-server
environment:
  - PUID=1000
  - PGID=1000
  - TZ=Asia/Shanghai
  - PASSWORD=password
  - SUDO_PASSWORD=password
  - PROXY_DOMAIN=code-server.my.domain #optional
  - DEFAULT_WORKSPACE=/config/workspace #optional
volumes:
  - ./config:/config
ports:
  - 2441:8443
restart: unless-stopped

    配置代理和中文

  • 打开Visual Studio Code，点击Manage，在列表中选择Settings

  • 在弹出的搜索框中输入"proxy"，即可看到代理的配置项"Http:Proxy"

  • 宿主机获取docker0的ip: ip address | grep docker0

  • 然后docker内设置代理 http://docker0的ip:port 拓展内搜索zh-cn，安装中文界面拓展

    安装 conda

  • 回到WORKSPACE，ctrl+~ 调出终端

  • sudo sed -i 's/archive.ubuntu.com/mirrors.aliyun.com/g' /etc/apt/sources.list

  • sudo apt update

  • sudo apt install wget

  • 安装 conda

    安装nodejs

    conda create -n node -c conda-forge nodejs
conda activate node
npm config set registry https://registry.npmmirror.com

    使用git

    npm create astro@latest
git config --global user.email "youremail"
git config --global user.name "yourname"
git branch -M main && git add . && git commit -m 'Initial commit'
git remote add origin https://github.com/Limour-dev/chatGPT.git
git push --set-upstream origin main --force # Creating a personal access token
git config --global credential.helper cache
git push

    hello world

    ---
const search = Astro.url.searchParams.get('search')! || '';
---
<h1>{search}</h1>

  • Enabling SSR in Your Project

  • 编辑 chatGPT/src/pages/index.astro

  • npm run dev

  • 访问 https://vscode.domain/proxy/3000/?search=hello%20world 进行测试

    安装 Jupyter

    持久化镜像存储

    mkdir -p ~/datascience && cd ~/datascience
nano docker-compose.yml
sudo docker-compose up -d
sudo docker-compose logs
sudo docker cp -a jupyterR:/opt /home/limour/upload/opt
sudo docker cp -a jupyterR:/home/jovyan /home/limour/upload/home
sudo docker-compose down && sudo docker volume prune

    version: '3.3'
services:
datascience-notebook:
    ports:
        - '57002:8888'
    container_name: jupyterR
    restart: always
    image: 'jupyter/datascience-notebook:r-4.3.1'
    command: start-notebook.sh --NotebookApp.token='***'

    启动镜像

    nano docker-compose.yml
sudo chmod 777 -R /home/limour/upload/
sudo docker-compose up -d
sudo docker-compose logs

    version: '3.3'
services:
datascience-notebook:
    ports:
        - '57002:8888'
    container_name: jupyterR
    restart: always
    volumes:
        - '/home/limour/upload:/home/jovyan/upload'
        - '/home/limour/upload/opt:/opt'
        - '/home/limour/upload/home:/home/jovyan'
    image: 'jupyter/datascience-notebook:r-4.3.1'
    command: start-notebook.sh --NotebookApp.token='***'

  • NPS内网穿透加NPM面板反代

    R包镜像

    nano .Rprofile
options()$repos ## 查看使用install.packages安装时的默认镜像
options()$BioC_mirror ##查看使用bioconductor的默认镜像

    options(BioC_mirror="https://mirrors.ustc.edu.cn/bioc/") ##指定镜像，这个是中国科技大学镜像
options("repos" = c(CRAN="https://mirrors.tuna.tsinghua.edu.cn/CRAN/")) ##指定install.packages安装镜像，这个是清华镜像
options(ggrepel.max.overlaps = Inf)

    安装 R 内核

    conda create -n seurat -c conda-forge r-seurat=4.1.1 -y
conda activate seurat
conda install -c conda-forge r-tidyverse -y
conda install -c conda-forge r-irkernel -y
Rscript -e "IRkernel::installspec(name='seurat', displayname='r-seurat')"
conda install -c conda-forge r-devtools -y
Rscript -e "BiocManager::install('glmGamPoi')"
wget -e "https_proxy=http://172.17.0.1:8580" https://github.com/chris-mcginnis-ucsf/DoubletFinder/archive/refs/heads/master.zip -O DoubletFinder-master.zip
Rscript -e "devtools::install_local('DoubletFinder-master.zip')"

    安装 python 内核

    conda create -n markdown2pptx -c conda-forge python -y
conda install -n markdown2pptx ipykernel -c conda-forge -y
conda run -n markdown2pptx python -m ipykernel install --user --name markdown2pptx
conda run -n markdown2pptx pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple

    安装 Golang 内核

  • 项目地址 gophernotes

    conda create -n golang -c conda-forge go -y
conda activate golang
go env -w GO111MODULE=on
go env -w GOPROXY=https://mirrors.aliyun.com/goproxy/
go install github.com/gopherdata/gophernotes@v0.7.5 #去仓库查看最新版本号
mkdir -p ~/.local/share/jupyter/kernels/golang
cd ~/.local/share/jupyter/kernels/golang
cp "$(go env GOPATH)"/pkg/mod/github.com/gopherdata/gophernotes@v0.7.5/kernel/* "."
chmod +w ./kernel.json
sed "s|gophernotes|$(go env GOPATH)/bin/gophernotes|" < kernel.json.in > kernel.json

    安装 jupyter-ai 内核

  • 获取端点和令牌

  • 填写端点时尾部需要加上 /v1

    conda create -n jupyter-ai -c conda-forge jupyter-ai-magics -y
conda install -n jupyter-ai -c conda-forge openai -y
conda install -n jupyter-ai ipykernel -c conda-forge -y
conda run -n jupyter-ai python -m ipykernel install --user --name jupyter-ai
# pip install --upgrade jupyterlab -i https://pypi.tuna.tsinghua.edu.cn/simple # 升级到 JupyterLab 4
# pip install jupyter_ai -i https://pypi.tuna.tsinghua.edu.cn/simple

  • 启用拓展并配置端点和令牌

    %load_ext jupyter_ai_magics
%env OPENAI_API_BASE=https://xxx/v1
%env OPENAI_API_KEY=sk-xxx

  • 示例

    %%ai chatgpt -f code
解决汉诺塔问题的函数

安装 rstudio

mkdir -p ~/app/rstudio && cd ~/app/rstudio && nano docker-compose.yml
sudo docker-compose up -d && sudo docker-compose logs

version: '3'
services:
  rstudio:
    image: dceoy/rstudio-server
    container_name: Rstudio
    deploy:
      resources:
        limits:
          cpus: '0.50'
          memory: 500M
        reservations:
          cpus: '0.25'
          memory: 200M
    restart: always
    ports:
      - 57022:8787
    volumes:
      - /home/gene/zl_liu/rstudio:/home/rstudio
      - /home/gene/upload:/home/rstudio/upload
    working_dir: /home/rstudio

更改 R 版本

  • 安装 conda

    # 容器内
conda create -n r_4_1_3 -c conda-forge r-base=4.1.3 -y
conda activate r_4_1_3
whereis R
# /home/rstudio/miniconda3/envs/r_4_1_3/bin/R
# 容器外
docker exec -it Rstudio /bin/bash
chmod 777 -R  /etc/rstudio/
exit 
nano -K /etc/rstudio/rserver.conf
# Server Configuration File
rsession-which-r=/home/rstudio/miniconda3/envs/r_4_1_3/bin/R
sudo docker-compose restart

    安装 seurat

    # 进入terminal，以下操作均在terminal中进行
export R_LIBS_SITE=""
# 在terminal中进入R
.libPaths('/home/rstudio/miniconda3/envs/r_4_1_3/lib/R/library')
.libPaths() 确保没有其他路径
remove.packages("vctrs")
install.packages("vctrs")
install.packages('Seurat')
remove.packages("cli")
install.packages("cli")
install.packages("tidyverse")
install.packages("plotly")
重启R session
library(tidyverse)
library(Seurat)

    绘制 3D-umap

    library(plotly)
library(Seurat)
sample13 <- readRDS("~/upload/zl_liu/work/Prognosis/scRNA/sample13.rds")
sample13 <- RunUMAP(sample13, dims = 1:10, n.components = 3L)
plot.data <- FetchData(object = sample13, vars = c("UMAP_1", "UMAP_2", "UMAP_3", "seurat_clusters"))
plot.data$label <- paste(rownames(plot.data))
# Plot your data, in this example my Seurat object had 21 clusters (0-20)
plot_ly(data = plot.data, 
    x = ~UMAP_1, y = ~UMAP_2, z = ~UMAP_3, 
    color = ~seurat_clusters, 
    colors = c("lightseagreen",
               "gray50",
               "darkgreen",
               "red4",
               "red",
               "turquoise4",
               "black",
               "yellow4",
               "royalblue1",
               "lightcyan3",
               "peachpuff3",
               "khaki3",
               "gray20",
               "orange2",
               "royalblue4",
               "yellow3",
               "gray80",
               "darkorchid1",
               "lawngreen",
               "plum2",
               "darkmagenta")[1:7],
    type = "scatter3d", 
    mode = "markers", 
    marker = list(size = 5, width=2), # controls size of points
    text=~label, #This is that extra column we made earlier for which we will use for cell ID
    hoverinfo="text") #When you visualize your plotly object, hovering your mouse pointer over a point shows cell names

安装 notebook

mkdir -p ~/app/notebook && cd ~/app/notebook && nano docker-compose.yml
sudo docker-compose up -d && sudo docker-compose logs

version: '3'
services:
  notebook:
    image: jupyter/r-notebook
    container_name: notebook
    restart: unless-stopped
    environment:
      - DOCKER_STACKS_JUPYTER_CMD=nbclassic
      - TZ=Asia/Shanghai
      - JUPYTER_GATEWAY_REQUEST_TIMEOUT=600
      - JUPYTER_GATEWAY_CONNECT_TIMEOUT=600
    ports:
      - '57002:8888'
    volumes:
      - '/home/limour/upload:/home/jovyan/upload'
      - '/home/limour/upload/home:/home/jovyan'
    command: start-notebook.py --NotebookApp.token='***'

conda init
source activate
conda config --add envs_dirs /home/jovyan/upload/envs

proxy_connect_timeout   600s;
proxy_read_timeout      600s;
proxy_send_timeout      600s;
proxy_buffering         off;