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這裡我們跟Cufflinks的原理一緻，使用總的外顯子長度，并且去除過多的重疊的外顯子的部分。使用R語言,輸入為基因的GTF檔案
包的安裝
依賴data.table, IRanges,rtracklayer
install.packages("data.table")
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("rtracklayer")
BiocManager::install("IRanges") 複制
代碼
library(data.table)
library("IRanges")
require("rtracklayer")
hg19 <- readGFF("hg19.gencodev27.gtf")
anno <- setDT(hg19)
anno <- anno[type=="exon",]
setnames(anno,c("seqid","start","end","gene_name","exon_number"),c("Chr","ExonStart","ExonEnd","Gene","Exon_number"))
#mkdir bin and mean by bin
Exon_region <- unique(anno[,.(Chr,ExonStart,ExonEnd,Exon_number,Gene)])
Exon_region <- Exon_region[,{x <- IRanges(ExonStart,ExonEnd);y <- reduce(x); list(ExonStart=y@start,ExonEnd=y@start+y@width-1)},by=.(Gene,Chr)]
Exon_region[,Exon_num:=1:.N,by=Gene]
Exon_region <- Exon_region[,.(Chr,ExonStart,ExonEnd,Exon_num,Gene)]
Exon_len <- Exon_region[,.(ExonLen = ExonEnd - ExonStart + 1),by=.(Exon_num,Gene)]
gene_len <- Exon_len[,.(Length = sum(ExonLen)),by=Gene]
# write out
fwrite(Exon_region,file="All_hg19gene_exon.bed", sep = "\t", col.names = T)
fwrite(gene_len, file = "All_hg19gene_len.txt", sep = "\t", col.names = T)
~ 複制
結果檔案
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基因長度檔案 連結：https://pan.baidu.com/s/1NtfM_ESyNyaT-kVaKu0MyQ
提取碼：gy88
複制這段内容後打開百度網盤手機App，操作更友善哦
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合并後的外顯子區域檔案
連結：https://pan.baidu.com/s/1-IpuC_2N88Jx9m2g5fCqmA
提取碼：cevo
複制這段内容後打開百度網盤手機App，操作更友善哦
參考資料
https://www.cureffi.org/2013/09/12/counts-vs-fpkms-in-rna-seq/