单细胞学习小组003期 Day4

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用户11153857

修改于 2024-07-03 07:57:24

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修改于 2024-07-03 07:57:24

文章被收录于专栏：花花单细胞学习小组003

This section is the further study of single cell data analysis following the previous BIC.

This is the homework of Day 1.

1. Install R packages in batches

1. Set up the mirror, this is an alternative option

options("repos"="https://mirrors.ustc.edu.cn/CRAN/")

if(!require("BiocManager")) install.packages("BiocManager",update = F,ask = F)

options(BioC_mirror="https://mirrors.ustc.edu.cn/bioc/")

2. Define a vector for packages from cran

cran_packages <- c('tidyverse',
                   'msigdbr',
                   'patchwork',
                   'SeuratObject',
                   'Seurat'
)

3. Define a vector for packages from bioconductor

Biocductor_packages <- c('sva',
                         'monocle',
                         'GOplot',
                         'GSVA',
                         'plotmo',
                         'regplot',
                         'scRNAseq',
                         'BiocStyle',
                         'celldex',
                         'SingleR',
                         'BiocParallel'
)

4. Batch install packages from cran with a for loop

for (pkg in cran_packages){
  if (! require(pkg,character.only=T,quietly = T) ) {
    install.packages(pkg,ask = F,update = F)
    require(pkg,character.only=T) 
  }
}

5. Batch install packages from bioconductor with a for loop

for (pkg in Biocductor_packages){
  if (! require(pkg,character.only=T,quietly = T) ) {
    BiocManager::install(pkg,ask = F,update = F)
    require(pkg,character.only=T) 
  }
}

6. Reload all packages to confirm the staus of installation

for (pkg in c(Biocductor_packages,cran_packages)){
  require(pkg,character.only=T) 
}

7. Check Seurat version

packageVersion("Seurat")

2. Find the single cell data you need

1. The applications of single cell RNA-seq

Cell atlas construction

Cell typing, new cell type identification

Oncology, including heteralgenetiy, micro-environment, drug resistance, and stem cell diffrenciation of tumor cell

Neuroscience

Developmental biology

Immunology

https://jieandze1314-1322730577.cos.ap-guangzhou.myqcloud.com/blog/2024-06-17-021758.png

Cited from https://m.umu.com/session/article/3PSv8e9a?fwx=1

2. Public databases

1.Gene Expression Omnibus (GEO) by NIH

https://www.ncbi.nlm.nih.gov/geo/

2.Single Cell Portal by Broad Institute

https://singlecell.broadinstitute.org/single_cell

3.Human Cell Atlas

https://www.humancellatlas.org/

4.Single Cell Expression Atlas by EMBL-EBI

https://www.ebi.ac.uk/gxa/sc/home

5.UCSC Cell Browser by UCSC

https://cells.ucsc.edu/

Various formats, different format corresponds to the different way of reading, we can see this: https://mp.weixin.qq.com/s/W7szy-Kg6G1N1ENHNRjGiw.

原创声明：本文系作者授权腾讯云开发者社区发表，未经许可，不得转载。

如有侵权，请联系 cloudcommunity@tencent.com 删除。

学习笔记

原创声明：本文系作者授权腾讯云开发者社区发表，未经许可，不得转载。

如有侵权，请联系 cloudcommunity@tencent.com 删除。

学习笔记

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