下載NCBI的數(shù)據(jù)

下載網(wǎng)址如下：ftp://ftp.ncbi.nih.gov/pub/HomoloGene/
下載最新的homologene.data數(shù)據(jù)

讀取數(shù)據(jù)，我放到excel轉(zhuǎn)換為csv格式后進(jìn)行讀取

rt<-read.csv("~/CFJiang/Annotation/homologene.csv",header = F)

觀察數(shù)據(jù)

rt[1:20,1:6]
   V1    V2        V3              V4        V5             V6
1   3  9606        34           ACADM   4557231    NP_000007.1
2   3  9598    469356           ACADM 160961497 NP_001104286.1
3   3  9544    705168           ACADM 109008502 XP_001101274.1
4   3  9615    490207           ACADM 545503811 XP_005622188.1
5   3  9913    505968           ACADM 115497690 NP_001068703.1
6   3 10090     11364           Acadm   6680618    NP_031408.1
7   3 10116     24158           Acadm 292494885    NP_058682.2
8   3  7955    406283           acadm 390190229    NP_998175.2
9   3  7227     38864         CG12262  24660351    NP_648149.1
10  3  7165   1276346 AgaP_AGAP005662  58387602    XP_315683.2
11  3  6239    173979          acdh-8  17534899    NP_495142.1
12  3  6239    181758          acdh-7  17570075    NP_510789.1
13  3  8364 100494748           acadm 512837304 XP_002936129.2
14  5  9606        37          ACADVL   4557235    NP_000009.1
15  5  9598    455237          ACADVL 332847152 XP_003315394.1
16  5  9615    489463          ACADVL 345800108    XP_546581.3
17  5  9913    282130          ACADVL  27806205    NP_776919.1
18  5 10090     11370          Acadvl  23956084    NP_059062.1
19  5 10116     25363          Acadvl   6978435    NP_037023.1
20  5  7955    573723          acadvl  47086807    NP_997776.1

可以看到第一列（V1）可以歸納為一個(gè)簇，即不同物種的該基因理論是同源的。V2為種屬的編號(hào)，如human為9906，鼠為10090。V3 為基因的NCBI ID，V4為NCBI的基因名，V5為GI編號(hào)，GI編號(hào)具體參考這個(gè)網(wǎng)址。V6為refseq編號(hào)，編號(hào)含義可參考這個(gè)網(wǎng)址。

分別提取鼠與人的信息

human<-rt[rt[,2]==9606,]
mouse<-rt[rt[,2]==10090,]
write.csv(human,"human_id.csv")
write.csv(mouse,"mouse_id.csv")

所以說根據(jù)上述信息可以分別查看mouse和human對(duì)應(yīng)的ID信息。

從jax實(shí)驗(yàn)室MGI數(shù)據(jù)庫下載

我使用的是HMD_HumanPhenotype.rpt文件

suppressMessages(library(tidyverse))
human_mouse_id<-read.table("HMD_HumanPhenotype.rpt",sep = "\t")
human_mouse_id<-human_mouse_id[,c(1,5,4)]

colnames(human_mouse_id)<-c("Human_Symbol","Mouse_Symbol","Match_or_not")
human_mouse_id<- human_mouse_id %>% filter(Match_or_not=="yes")
human_mouse_id<-human_mouse_id[!duplicated(human_mouse_id$Mouse_Symbol),]
row.names(human_mouse_id)<-as.character(human_mouse_id$Mouse_Symbol)

write.csv(human_mouse_id,"~/Desktop/GoogleDrive/Annotation/human_mouse_homologene/HMD_HumanPhenotype.csv")