小鼠参考基因组id转换gtf文件chb注释官网下载相应的基因中注释文件gse155802 getmatrixgenecode 参考基因组下载序列比对 hg19 索引文件mapping referece

 参考基因组在很多网站都可以下载到

Index of /pub/release-93/gtf/mus_musculus (ensembl.org)http://ftp.ensembl.org/pub/release-93/gtf/mus_musculus/ 我想要研究的基因组

我怎么知道是这个的呢 ，因为这篇文献里面提到

References - 3.0.0 (November 19, 2018)

• Human reference, GRCh38 (Ensembl 93)
• Human reference, hg19 (Ensembl 87)https://support.10xgenomics.com/single-cell-gene-expression/software/release-notes/build#hg19_3.0.0
• Mouse reference, mm10 (Ensembl 93)

所以我就在cellranger官网上找到了这个Build Notes for Reference Packages -Software -Single Cell Gene Expression -Official 10x Genomics Support

点进去之后，出现代码

Mouse reference, mm10 (includes mouse V(D)J genes)
wget ftp://ftp.ensembl.org/pub/release-93/fasta/mus_musculus/dna/Mus_musculus.GRCm38.dna.primary_assembly.fa.gz
gunzip Mus_musculus.GRCm38.dna.primary_assembly.fa.gzwget ftp://ftp.ensembl.org/pub/release-93/gtf/mus_musculus/Mus_musculus.GRCm38.93.gtf.gz
gunzip Mus_musculus.GRCm38.93.gtf.gz

根据代码下载的地址  就可以找到自己要复现的基因组地址了！这里我只需要gtf格式就行啦

Index of /pub/release-93/gtf/mus_musculus (ensembl.org)

手动下载之后

如何处理gtf文件呢？在R语言中读取GTF文件的最好方法 · 大专栏 (dazhuanlan.com)

链接里给了好多方法  哈哈哈

我就用第一个吧 ，开始！

####参考基因组id转换gtf文件 https://www.dazhuanlan.com/insafe/topics/975998
#BiocManager::install("rtracklayer")
library(rtracklayer)#https://support.10xgenomics.com/single-cell-gene-expression/software/release-notes/build
#把Mus_musculus.GRCm38.93.gtf.gz下载下来 为什么下载这个呢？http://ftp.ensembl.org/pub/release-93/gtf/mus_musculus/
gtf_df=rtracklayer::import('Mus_musculus.GRCm38.93.gtf.gz')
getwd()

更改seurat行名 seurat基因名

如何给Seurat对象的基因重命名？【基因名转换】2022-07-27 - 简书 (jianshu.com)

#创建函数 改名字
RenameGenesSeurat <- function(obj , 
                              newnames ) { 
  # Replace gene names in different slots of a Seurat object. Run this before integration. Run this before integration. 
  # It only changes obj@assays$RNA@counts, @data and @scale.data.
  print("Run this before integration. It only changes obj@assays$RNA@counts, @data and @scale.data.")
  RNA <- obj@assays$RNA
  
  if (nrow(RNA) == length(newnames)) {
    if (length(RNA@counts)) RNA@counts@Dimnames[[1]]            <- newnames
    if (length(RNA@data)) RNA@data@Dimnames[[1]]                <- newnames
    if (length(RNA@scale.data)) RNA@scale.data@Dimnames[[1]]    <- newnames
  } else {"Unequal gene sets: nrow(RNA) != nrow(newnames)"}
  obj@assays$RNA <- RNA
  return(obj)
}

#教程地址
#https://cloud.tencent.com/developer/article/1697249#https://bioconductor.org/packages/release/data/experiment/vignettes/scRNAseq/inst/doc/scRNAseq.html
#https://mp.weixin.qq.com/mp/appmsgalbum?__biz=MzI1Njk4ODE0MQ==&action=getalbum&album_id=1326587538303434752&scene=173&from_msgid=2247484689&from_itemidx=1&count=3&nolastread=1#wechat_redirect
rm(list = ls()) 
Sys.setenv(R_MAX_NUM_DLLS=999)
options(stringsAsFactors = F)##########三对三的数据
1#准备原始分析数据  先手动下载  去浏览器下载文件到自己的文件夹下，然后解压
#https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi  
# 3个样本，共9个文件。需要分到9个文件夹里，并且重命名
getwd()
path="G:/silicosis/geo/GSE155802_scRNA-seq_AT2_sorted_mice_lung_chb/" #空间转录组
dir.create(path,recursive = T)
setwd(path)
getwd()??list.files
dirs_and_files=list.files(path = "./",all.files = T,pattern = ".csv",include.dirs = F,recursive = T)fs=grep(x=dirs_and_files,"GSE155802_RAW/GSM.+/",value = T)
fs
getwd()