统计fasta/fastq的序列长度及其分布展示

首先得到每条序列的长度，在这里使用seqkit软件。
seqkit软件是一个强大的序列处理工具，安装方法参见官方网站.
代码如下：

seqkit fx2tab -j 30 -l  -n -i -H file.fastq.gz  > Length.txt
#参数：
# -j 是线程数
#-B, --base-content value   要输出的碱基含量e.g. -B AT -B N
#-g, --gc                   print GC content
#-l, --length               print sequence length
#-n, --name                only print names
#-i, --only-id              print ID instead of full head
head  Length.txt  # 查看Length.txt

结果如下所示：

Length.txt

提取长度分布：

 seqkit fx2tab -j 30 -l  -n -i -H file.fastq.gz  |cut -f 2 > length.txt

将得到结果length.txt导入到R中绘制序列长度分布图，
代码如下：

library(tidyverse)

length <- read_tsv("Length.txt") %>% group_by(length) %>% summarise(Count = n())
sum <- sum(length$Count)
ggplot(length) + 
  geom_col(aes(length, Count), width = 0.8) + 
  geom_line(aes(length, Count), group = 1) + 
  geom_point(aes(length, Count)) + 
  scale_y_continuous(sec.axis = sec_axis(~.*100/sum, name = "% Relative Abundance")) + 
  xlab("R1.Length") +
  theme_bw() + theme(panel.grid = element_blank(), 
                     axis.title = element_text(size = 15))

ggsave("Length.png", height = 5, width = 8)
ggsave("Length.pdf", height = 5, width = 8)

结果如下：

图1

上图由于数据太多，去掉点和连线更清晰

library(tidyverse)

length <- read_tsv("Length.txt") %>% group_by(length) %>% summarise(Count = n())
sum <- sum(length$Count)
ggplot(length) + 
  geom_col(aes(length, Count), width = 0.8) + 
#  geom_line(aes(length, Count), group = 1) + 
#  geom_point(aes(length, Count)) + 
  scale_y_continuous(sec.axis = sec_axis(~.*100/sum, name = "% Relative Abundance")) + 
  xlab("Length") +
  theme_bw() + theme(panel.grid = element_blank(), 
                     axis.title = element_text(size = 15))

ggsave("Length.png", height = 5, width = 8)
ggsave("Length.pdf", height = 5, width = 8)

结果如下：

图2

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参考：https://www.jianshu.com/p/31244fb42da1