R package for intersting🐭
library(devtools)
install_github("caokai001/kcaoplot")
library(kcaoplot)
尝试使用R包，写小函数🐻
test_ggplot(6)
- test_plot(4)
- hello()
目的：
从癌症组织中snp.vcf, 可以猜想snp 分布也许不是随机的，于是可以尝试研究是否到某个motif附近富集。
input file:
- mynew.txt : Fimo.tsv file;use FIMO to scan hg19.fa
- NHEK_merge_ctcf.bed : CTCF peak 文件或者Dnase peak 文件
- hg19_uv_snp_pos.bed ： snp 文件
# UV
ctcf.motif=Fimo2GRanges("mynew.txt","GRanges")
NHEK.peak=bed2GRanges("./ctcf_peak/NHEK_merge_ctcf.bed",header=FALSE)
# snptogr
somatic_COLO829=bed2GRanges("hg19_uv_snp_pos.bed",header=FALSE)
names(mcols(somatic_COLO829)) <-c("Ref","Alt")
somatic_COLO829$id=c(1:length(somatic_COLO829))
# filter_fimo
motif.ovl=filter_fimo(NHEK.peak,ctcf.motif)
# 拓宽到1000bp
filter_fimo_to_1000bp_gr(motif.ovl)
# snp 落到区间位置
mut.table<-mut_pos_tb(site,somatic_COLO829)
# 画图1000bp
plot_mutation_loci(mut.table)
# 画图flank 5bp
plot_flank_5bp(motif.ovl,somatic_COLO829)
# 读入ctcf.motif
ctcf.motif=Fimo2GRanges("mynew.txt","GRanges")
# 开放区域合并
dnase.peak<-bed2GRanges("E094-DNase.all.peaks.v2.bed")
dnase.fdr<-bed2GRanges("E094-DNase.fdr0.01.peaks.v2.bed")
dnase.mac<-bed2GRanges("E094-DNase.macs2.narrowPeak")
dnase=c(dnase.peak,dnase.fdr,dnase.mac)
# 取并集
library(GenomicRanges)
dnase=reduce(dnase)
# 读入snp信息
somatic_gastric<-bed2GRanges("41467_2018_3828_MOESM6_ESM.txt",header=TRUE)
names(mcols(somatic_gastric))[1:2]<-c("Ref","Alt")
somatic_gastric$id=c(1:length(somatic_gastric))
# 过滤FIMO
motif.ovl<-filter_fimo(dnase,ctcf.motif)
# 拓展到1kb
site=filter_fimo_to_1000bp_gr(motif.ovl)
# 与突变位置取交集
mut.table<-mut_pos_tb(site,somatic_gastric)
# 画1kp 区间突变分布图
plot_mutation_loci(mut.table)
# 画flank_5bp 区间分布图
plot_flank_5bp(motif.ovl,somatic_gastric)