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VCF文件的变异分布图，除了使用Circos图之外，统计特定材料间的变异分布情况时可能会用到染色体分布图，为了节省时间，实现统计及绘图的自动化，现提供统计数量用的Python脚本和绘图使用的R脚本，仅供参考。如有其它更快捷的方法，或觉得脚本太拙劣，欢迎留言批评交流。
image
PYTHON脚本，使用脚本整理100Kb滑窗中变异位点数量：
variation_number_in_bin.py
import sys
input_file = sys.argv[1]
step_len = 100000
result = {}
chrom_stats = {
"Chr1":43270923,
"Chr2":35937250,
"Chr3":36413819,
"Chr4":35502694,
"Chr5":29958434,
"Chr6":31248787,
"Chr7":29697621,
"Chr8":28443022,
"Chr9":23012720,
"Chr10":23207287,
"Chr11":29021106,
"Chr12":27531856
}
for chrom in chrom_stats.keys():
step= 0
step_start = 0
result[chrom]={}
result[chrom][step]=0
for line in open(input_file):
if line.startswith(chrom):
pos = line.split()[1]
if step_start < int(pos) < (step_start + step_len):
result[chrom][step] += 1
if int(pos) >= (step_start + step_len):
step += 1
step_start += step_len
result[chrom][step] = 0
result[chrom][step] += 1
for steps,nums in result[chrom].items():
print(chrom, steps, nums, sep="\t")
image
下面画图，使用R脚本如下：
library(ggplot2)
library(Cairo)
var_density <- read.table("snp.distribution.stats", sep = "\t", header = T)
names(var_density) <- c("chrom", "region", "variation_count")
var_density$chrom <- factor(var_density$chrom, levels=c(
"Chr1", "Chr2", "Chr3", "Chr4", "Chr5", "Chr6",
"Chr7", "Chr8", "Chr9", "Chr10", "Chr11", "Chr12"))
CairoPNG(filename = "variation_distribution.png", width = 12000, height = 7500, res = 600)
distribution <- ggplot(var_density, aes(x=region, y=variation_count))
distribution + geom_line(colour = "darkorange4", size = 0.35) +
guides(fill=FALSE) +
theme(axis.line = element_line(size=0.5),
panel.background = element_rect(fill="white",size=rel(20)),
panel.grid.minor = element_line(colour = "gray"),
axis.text = element_text(family="Times New Roman",size=16,face="bold"),
axis.title = element_text(family="Times New Roman",size=18,face="bold"),
strip.text = element_text(family="Times New Roman",size=12,face="bold")) +
facet_wrap(~chrom, ncol=2)
dev.off()
作者：生物数据分析笔记
链接：https://www.jianshu.com/p/9b5541a3f67c
来源：简书
著作权归作者所有。商业转载请联系作者获得授权，非商业转载请注明出处。
