生信基础 | 人-小鼠基因之间的比较
先看看MSigDB中的基因ENTREZID是否可以全部转化为SYMBOL。
library(biomaRt)
library(clusterProfiler)
library(org.Hs.eg.db)
library(org.Mm.eg.db)
library(AnnotationDbi)
load("F:/BioInfoStudy/data/genesets/mouse_H_v5p2.rdata")
load("F:/BioInfoStudy/data/genesets/human_H_v5p2.rdata")
hsa_ent <- c()
for(x in names(Hs.H)){
hsa_ent <- c(hsa_ent,Hs.H[[x]])
}
hsa_ent <- unique(hsa_ent)
length(hsa_ent)
hsa_ent2symb <- bitr(hsa_ent,
fromType = "ENTREZID",
toType = "SYMBOL",
OrgDb = org.Hs.eg.db)
dim(hsa_ent2symb)
diff_ent <- setdiff(hsa_ent,hsa_ent2symb$ENTREZID)
ent2symb <- toTable(org.Hs.egSYMBOL)
ent2symb[match(diff_ent,ent2symb$gene_id),]
AnnotationDbi::select(org.Hs.eg.db,
keys=diff_ent,columns=c("SYMBOL"),
keytype="ENTREZID" )
mget(diff_ent,
org.Hs.egSYMBOL,
ifnotfound=NA
通过多种转换方式,发现人的ENTREZID有3个无法找到对应的SYMBOL,NCBI上检索了一下,也没找到这3个基因。
> diff_ent
[1] "285464" "11217" "80761"
再看看小鼠的。
###--------------------------------------小鼠
mus_ent <- c()
for(x in names(Mm.H)){
mus_ent <- c(mus_ent,Mm.H[[x]])
}
mus_ent <- unique(mus_ent)
length(mus_ent)
mus_ent2symb <- bitr(mus_ent,
fromType = "ENTREZID",
toType = "SYMBOL",
OrgDb = org.Mm.eg.db)
dim(mus_ent2symb)
diff_ent <- setdiff(mus_ent,mus_ent2symb$ENTREZID)
ent2symb <- toTable(org.Hs.egSYMBOL)
ent2symb[match(diff_ent,ent2symb$gene_id),]
AnnotationDbi::select(org.Hs.eg.db,
keys=diff_ent,columns=c("SYMBOL"),
keytype="ENTREZID" )
#org.Mm.egMAPCOUNTS
mget(diff_ent,
org.Mm.egSYMBOL,
ifnotfound=NA)
居然有15个没有找到对应的symbol。
> diff_ent
[1] "675165" "100038993" "100861969" "100043385" "100504735" "105245585" "546061"
[8] "625758" "668131" "665343" "667941" "11641" "100039053" "100043918"
[15] "100043921"
写一个函数,用于人-小鼠同源基因的转换;
####------------------------------
conversion_BtHsaAndMusGenes <- function(genes,species){
human <- biomaRt::useMart(biomart = "ENSEMBL_MART_ENSEMBL",
dataset = "hsapiens_gene_ensembl")
mouse <- biomaRt::useMart(biomart = "ENSEMBL_MART_ENSEMBL",
dataset = "mmusculus_gene_ensembl")
if(species == "human"){
gt <- biomaRt::getLDS(attributes = c("hgnc_symbol"),
filters = "hgnc_symbol",
values = genes,
mart = human,
attributesL = c("mgi_symbol"),
martL = mouse,uniqueRows = T)
}else if(species == "mouse"){
gt <- biomaRt::getLDS(attributes = c("mgi_symbol"),
filters = "mgi_symbol",
values = genes , mart = mouse,
attributesL = c("hgnc_symbol"),
martL = human, uniqueRows=T)
}else{stop("Wrong species information")}
return(gt)
}
加载我自己从gtf文件读入的所有基因信息进行转换。
load(file = "K:/BioInfoFiles/human/gencode.v35_human_hsaGeneInfo.Rdata")
head(hsaGeneInfo)[1:3,]
# > head(hsaGeneInfo)
# ensembl symbol gene_type geneLength
# 1 ENSG00000000003 TSPAN6 protein_coding 4536
# 2 ENSG00000000005 TNMD protein_coding 1476
# 3 ENSG00000000419 DPM1 protein_coding 1207
load(file = "K:/BioInfoFiles//mouse/gencode.vM27_mouse_musGeneInfo.Rdata")
head(musGeneInfo)
# > head(musGeneInfo)[1:4,]
# ensembl symbol gene_type geneLength
# 1 ENSMUSG00000000001 Gnai3 protein_coding 3262
# 2 ENSMUSG00000000003 Pbsn protein_coding 902
# 3 ENSMUSG00000000028 Cdc45 protein_coding 3506
# 4 ENSMUSG00000000031 H19 lncRNA 2460
###把小鼠基因转换为人的同源基因
m2h <- conversion_BtHsaAndMusGenes(genes = musGeneInfo$symbol,species = "mouse")
head(m2h)
# > head( m2h)[1:2,]
# MGI.symbol HGNC.symbol
# 1 mt-Atp6 MT-ATP6
# 2 mt-Co2 MT-CO2
dim(m2h)
# > dim(m2h)
# [1] 23075 2
###把人基因转换为小鼠的同源基因
h2m <- conversion_BtHsaAndMusGenes(genes = hsaGeneInfo$symbol,species = "human")
h2m[1:2,]
# > h2m[1:2,]
# HGNC.symbol MGI.symbol
# 1 MT-CO2 mt-Co2
# 2 MT-CO1 mt-Co1
dim(h2m)
# > dim(h2m)
# [1] 22714 2
##有重复的
length(unique(m2h$HGNC.symbol))
length(unique(m2h$MGI.symbol))
# > length(unique(m2h$HGNC.symbol))
# [1] 18411
# > length(unique(m2h$MGI.symbol))
# [1] 19308
这里比较MSigDB数据集中小鼠与人基因之间的差异并统计。
statgeneinfo <- data.frame()
identical(names(Hs.H),names(Mm.H))
#gs <- names(Mm.H)[1]
for(gs in names(Mm.H)){
total_pre_hsa <- length(Hs.H[[gs]])
total_pre_mus <- length(Mm.H[[gs]])
hsa_symbol <- bitr(Hs.H[[gs]],
fromType = "ENTREZID",
toType = "SYMBOL",
OrgDb = org.Hs.eg.db)[,2] %>% na.omit()
total_after_hsa <- length(hsa_symbol)
mus_symbol <- bitr(Mm.H[[gs]],
fromType = "ENTREZID",
toType = "SYMBOL",
OrgDb = org.Mm.eg.db)[,2] %>% na.omit()
total_after_mus <- length(mus_symbol)
hsa_mus_con_g <- intersect(hsa_symbol,m2h[match(mus_symbol,mus_ent2symb$SYMBOL),2])
hsa_mus_con_len <- length(hsa_mus_con_g)
hsa_uniq <- total_pre_hsa - hsa_mus_con_len
mus_uniq <- total_pre_mus - hsa_mus_con_len
hsa_na <- total_pre_hsa - total_after_hsa
mus_na <- total_pre_mus - total_after_mus
info <- data.frame(dataset = gs,
total_pre_hsa = total_pre_hsa,
total_pre_mus = total_pre_mus,
total_after_hsa = total_after_hsa,
total_after_mus = total_after_mus,
hsa_mus_con_len = hsa_mus_con_len,
hsa_uniq = hsa_uniq,
mus_uniq = mus_uniq,
hsa_na = hsa_na,
mus_na = mus_na)
statgeneinfo <- rbind(statgeneinfo,info)
}
total_pre_hsa和total_pre_mus:原始数据集中的基因个数
total_after_hsa和total_after_mus:进行基因转换后的基因个数
hsa_mus_con_len:人和小鼠共有的基因个数
hsa_uniq和mus_uniq:人和小鼠中各特有的基因个数。
hsa_na和mus_na:未能将ENTREZID转化为SYMBOL的个数
参考:
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