获取字符串中特定位置的多个字符替换的所有组合
Get all combinations of multiple characters substitution at specific positions within a string
我有一个像下面这样的 data.table，它包含 DNA 字符串组（ref_seq 列）和一系列突变（alt 列中的字符）及其相关沿字符串的位置（snp_position 列）。
因为n突变，得到的字符串数是2^n，我想做的是做一个通用函数，允许生成 ref_seq 字符串中 snp_position 处替换的 alt 字符的所有组合，同时（最好）保持此 data.frame 结构
> dt
seqnames hap_start hap_end snp alt snp_position numb_snps_per_hap
1: chr1 19600274 19600443 19600324 G 50 4
2: chr1 19600274 19600443 19600378 C 104 4
3: chr1 19600274 19600443 19600389 A 115 4
4: chr1 19600274 19600443 19600396 C 122 4
5: chr10 5482730 5482899 5482790 C 60 4
6: chr10 5482730 5482899 5482830 A 100 4
7: chr10 5482730 5482899 5482839 A 109 4
8: chr10 5482730 5482899 5482843 A 113 4
ref_seq
1: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACCGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATTCGGAGCCCCAGGCCGCCAAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
2: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACCGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATTCGGAGCCCCAGGCCGCCAAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
3: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACCGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATTCGGAGCCCCAGGCCGCCAAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
4: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACCGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATTCGGAGCCCCAGGCCGCCAAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
5: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTGTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTTACTAGTGAGTGAGTCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
6: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTGTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTTACTAGTGAGTGAGTCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
7: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTGTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTTACTAGTGAGTGAGTCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
8: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTGTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTTACTAGTGAGTGAGTCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
> dput(dt)
structure(list(seqnames = c("chr1", "chr1", "chr1", "chr1", "chr10",
"chr10", "chr10", "chr10"), hap_start = c(19600274, 19600274,
19600274, 19600274, 5482730, 5482730, 5482730, 5482730), hap_end = c(19600443,
19600443, 19600443, 19600443, 5482899, 5482899, 5482899, 5482899
), snp = c(19600324L, 19600378L, 19600389L, 19600396L, 5482790L,
5482830L, 5482839L, 5482843L), alt = c("G", "C", "A", "C", "C",
"A", "A", "A"), snp_position = c(50, 104, 115, 122, 60, 100,
109, 113), numb_snps_per_hap = c(4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L), ref_seq = c("CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACCGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATTCGGAGCCCCAGGCCGCCAAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC",
"CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACCGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATTCGGAGCCCCAGGCCGCCAAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC",
"CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACCGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATTCGGAGCCCCAGGCCGCCAAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC",
"CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACCGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATTCGGAGCCCCAGGCCGCCAAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC",
"TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTGTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTTACTAGTGAGTGAGTCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT",
"TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTGTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTTACTAGTGAGTGAGTCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT",
"TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTGTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTTACTAGTGAGTGAGTCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT",
"TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTGTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTTACTAGTGAGTGAGTCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT"
)), row.names = c(NA, -8L), class = c("data.table", "data.frame"
), sorted = "seqnames", .internal.selfref = <pointer: 0x1d50f80>)
期望的输出
> dt_final
seqnames hap_start hap_end
1: chr1 19600274 19600443
2: chr1 19600274 19600443
3: chr1 19600274 19600443
4: chr1 19600274 19600443
5: chr1 19600274 19600443
6: chr1 19600274 19600443
7: chr1 19600274 19600443
8: chr1 19600274 19600443
9: chr1 19600274 19600443
10: chr1 19600274 19600443
11: chr1 19600274 19600443
12: chr1 19600274 19600443
13: chr1 19600274 19600443
14: chr1 19600274 19600443
15: chr1 19600274 19600443
16: chr1 19600274 19600443
17: chr10 5482730 5482899
18: chr10 5482730 5482899
19: chr10 5482730 5482899
20: chr10 5482730 5482899
21: chr10 5482730 5482899
22: chr10 5482730 5482899
23: chr10 5482730 5482899
24: chr10 5482730 5482899
25: chr10 5482730 5482899
26: chr10 5482730 5482899
27: chr10 5482730 5482899
28: chr10 5482730 5482899
29: chr10 5482730 5482899
30: chr10 5482730 5482899
31: chr10 5482730 5482899
32: chr10 5482730 5482899
seqnames hap_start hap_end
sequence
1: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACCGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATTCGGAGCCCCAAGCCGCCCAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
2: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACGGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATCCGGAGCCCCAGGCCGCCAAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
3: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACGGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATTCGGAGCCCCAAGCCGCCAAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
4: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACCGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATCCGGAGCCCCAGGCCGCCCAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
5: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACGGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATCCGGAGCCCCAAGCCGCCCAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
6: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACGGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATCCGGAGCCCCAAGCCGCCCAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
7: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACGGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATCCGGAGCCCCAAGCCGCCCAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
8: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACGGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATCCGGAGCCCCAAGCCGCCCAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
9: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACGGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATTCGGAGCCCCAGGCCGCCAAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
10: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACCGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATCCGGAGCCCCAGGCCGCCAAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
11: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACCGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATTCGGAGCCCCAAGCCGCCAAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
12: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACCGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATTCGGAGCCCCAGGCCGCCCAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
13: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACCGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATCCGGAGCCCCAAGCCGCCCAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
14: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACGGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATTCGGAGCCCCAAGCCGCCCAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
15: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACGGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATCCGGAGCCCCAGGCCGCCCAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
16: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACGGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATCCGGAGCCCCAAGCCGCCAAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
17: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTGTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTTACTAGTGAATGAATCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
18: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTCTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTAACTAGTGAGTGAGTCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
19: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTCTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTTACTAGTGAATGAGTCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
20: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTGTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTAACTAGTGAGTGAATCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
21: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTCTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTAACTAGTGAATGAATCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
22: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTCTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTAACTAGTGAATGAATCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
23: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTCTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTAACTAGTGAATGAATCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
24: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTCTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTAACTAGTGAATGAATCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
25: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTCTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTTACTAGTGAGTGAGTCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
26: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTGTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTAACTAGTGAGTGAGTCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
27: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTGTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTTACTAGTGAATGAGTCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
28: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTGTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTTACTAGTGAGTGAATCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
29: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTGTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTAACTAGTGAATGAATCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
30: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTCTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTTACTAGTGAATGAATCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
31: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTCTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTAACTAGTGAGTGAATCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
32: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTCTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTAACTAGTGAATGAGTCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
sequence
你知道如何在 R 中执行此操作吗？
谢谢
我只使用了前两行和感兴趣的列。我还减小了 refseq 的大小并使用 snp_position=2 以获得更好的可视化效果。但是，只要列名相同，它就会对您的完整数据同样有效。
输入：
df <- data.frame(alt=c("G","A"),snp_position=c(2,2),refseq=c("CCAGGGAGAGCGGGGCAGCGC",
"TCAGGGAGAGCGGGGCAGCGC"))
函数：
seq_mut <- function(refseq,snp_position,Mutated_allele){
combinations <- c("A","T","C","G")
WT_allele <- substr(refseq, snp_position, snp_position)
combinations <- combinations[combinations!=WT_allele]
refseq2 <- refseq
substr(refseq2, snp_position, snp_position) <- Mutated_allele
combinations <- combinations[combinations!=Mutated_allele]
seq <- refseq2
for(variant in combinations){
refseq2 <- refseq
substr(refseq2, snp_position, snp_position) <- variant
seq <- paste0(seq,";",refseq2)
}
return(seq)
}
与 dplyr:
library(dplyr)
df <- df %>% rowwise() %>% mutate(ref_seq_mut=seq_mut(refseq,snp_position,alt))
整理师：
library(tidyr)
df <- df %>% separate(ref_seq_mut,into=c("V1","V2","V3"))%>%
pivot_longer(cols=refseq:V3,values_to="refseq") %>% select(-name)
输出：
alt snp_position refseq
<chr> <dbl> <chr>
1 G 2 CCAGGGAGAGCGGGGCAGCGC
2 G 2 CGAGGGAGAGCGGGGCAGCGC
3 G 2 CAAGGGAGAGCGGGGCAGCGC
4 G 2 CTAGGGAGAGCGGGGCAGCGC
5 A 2 TCAGGGAGAGCGGGGCAGCGC
6 A 2 TAAGGGAGAGCGGGGCAGCGC
7 A 2 TTAGGGAGAGCGGGGCAGCGC
8 A 2 TGAGGGAGAGCGGGGCAGCGC
这是一个使用简化示例输入数据的选项。很多步骤说的太详细了，尽量运行一点一点的了解每个功能吧。
基本上，我在 refseq 上进行拆分，然后将 refseq 拆分为字母，然后使用 更新位置组合alt，然后粘贴回去。
df <- data.frame(alt = c("A","B", "C", "D", "E"),
snp_position = c(2, 4, 1, 3, 5),
refseq = c("-----", "-----",
"=====", "=====", "====="),
stringsAsFactors = FALSE)
res <- stack(
lapply(split(df, df$refseq), function(i){
s <- strsplit(i$refseq[ 1 ], "")[[ 1 ]]
pos <- i$snp_position
alt <- i$alt
unlist(
lapply(seq(nrow(i)), function(j)
combn(pos, j,
FUN = function(k){
res <- s
res[ k ] <- alt[ which(pos %in% k) ]
paste(res, collapse = "")
}))
)
}))
colnames(res) <- c("sequence", "refseq")
res
# sequence refseq
# 1 -A--- -----
# 2 ---B- -----
# 3 -A-B- -----
# 4 C==== =====
# 5 ==D== =====
# 6 ====E =====
# 7 C=D== =====
# 8 C===E =====
# 9 ==D=E =====
# 10 C=D=E =====
我有一个像下面这样的 data.table，它包含 DNA 字符串组（ref_seq 列）和一系列突变（alt 列中的字符）及其相关沿字符串的位置（snp_position 列）。
因为n突变，得到的字符串数是2^n，我想做的是做一个通用函数，允许生成 ref_seq 字符串中 snp_position 处替换的 alt 字符的所有组合，同时（最好）保持此 data.frame 结构
> dt
seqnames hap_start hap_end snp alt snp_position numb_snps_per_hap
1: chr1 19600274 19600443 19600324 G 50 4
2: chr1 19600274 19600443 19600378 C 104 4
3: chr1 19600274 19600443 19600389 A 115 4
4: chr1 19600274 19600443 19600396 C 122 4
5: chr10 5482730 5482899 5482790 C 60 4
6: chr10 5482730 5482899 5482830 A 100 4
7: chr10 5482730 5482899 5482839 A 109 4
8: chr10 5482730 5482899 5482843 A 113 4
ref_seq
1: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACCGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATTCGGAGCCCCAGGCCGCCAAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
2: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACCGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATTCGGAGCCCCAGGCCGCCAAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
3: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACCGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATTCGGAGCCCCAGGCCGCCAAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
4: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACCGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATTCGGAGCCCCAGGCCGCCAAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
5: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTGTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTTACTAGTGAGTGAGTCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
6: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTGTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTTACTAGTGAGTGAGTCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
7: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTGTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTTACTAGTGAGTGAGTCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
8: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTGTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTTACTAGTGAGTGAGTCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
> dput(dt)
structure(list(seqnames = c("chr1", "chr1", "chr1", "chr1", "chr10",
"chr10", "chr10", "chr10"), hap_start = c(19600274, 19600274,
19600274, 19600274, 5482730, 5482730, 5482730, 5482730), hap_end = c(19600443,
19600443, 19600443, 19600443, 5482899, 5482899, 5482899, 5482899
), snp = c(19600324L, 19600378L, 19600389L, 19600396L, 5482790L,
5482830L, 5482839L, 5482843L), alt = c("G", "C", "A", "C", "C",
"A", "A", "A"), snp_position = c(50, 104, 115, 122, 60, 100,
109, 113), numb_snps_per_hap = c(4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L), ref_seq = c("CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACCGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATTCGGAGCCCCAGGCCGCCAAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC",
"CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACCGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATTCGGAGCCCCAGGCCGCCAAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC",
"CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACCGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATTCGGAGCCCCAGGCCGCCAAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC",
"CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACCGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATTCGGAGCCCCAGGCCGCCAAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC",
"TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTGTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTTACTAGTGAGTGAGTCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT",
"TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTGTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTTACTAGTGAGTGAGTCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT",
"TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTGTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTTACTAGTGAGTGAGTCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT",
"TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTGTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTTACTAGTGAGTGAGTCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT"
)), row.names = c(NA, -8L), class = c("data.table", "data.frame"
), sorted = "seqnames", .internal.selfref = <pointer: 0x1d50f80>)
期望的输出
> dt_final
seqnames hap_start hap_end
1: chr1 19600274 19600443
2: chr1 19600274 19600443
3: chr1 19600274 19600443
4: chr1 19600274 19600443
5: chr1 19600274 19600443
6: chr1 19600274 19600443
7: chr1 19600274 19600443
8: chr1 19600274 19600443
9: chr1 19600274 19600443
10: chr1 19600274 19600443
11: chr1 19600274 19600443
12: chr1 19600274 19600443
13: chr1 19600274 19600443
14: chr1 19600274 19600443
15: chr1 19600274 19600443
16: chr1 19600274 19600443
17: chr10 5482730 5482899
18: chr10 5482730 5482899
19: chr10 5482730 5482899
20: chr10 5482730 5482899
21: chr10 5482730 5482899
22: chr10 5482730 5482899
23: chr10 5482730 5482899
24: chr10 5482730 5482899
25: chr10 5482730 5482899
26: chr10 5482730 5482899
27: chr10 5482730 5482899
28: chr10 5482730 5482899
29: chr10 5482730 5482899
30: chr10 5482730 5482899
31: chr10 5482730 5482899
32: chr10 5482730 5482899
seqnames hap_start hap_end
sequence
1: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACCGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATTCGGAGCCCCAAGCCGCCCAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
2: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACGGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATCCGGAGCCCCAGGCCGCCAAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
3: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACGGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATTCGGAGCCCCAAGCCGCCAAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
4: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACCGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATCCGGAGCCCCAGGCCGCCCAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
5: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACGGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATCCGGAGCCCCAAGCCGCCCAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
6: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACGGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATCCGGAGCCCCAAGCCGCCCAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
7: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACGGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATCCGGAGCCCCAAGCCGCCCAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
8: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACGGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATCCGGAGCCCCAAGCCGCCCAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
9: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACGGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATTCGGAGCCCCAGGCCGCCAAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
10: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACCGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATCCGGAGCCCCAGGCCGCCAAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
11: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACCGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATTCGGAGCCCCAAGCCGCCAAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
12: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACCGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATTCGGAGCCCCAGGCCGCCCAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
13: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACCGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATCCGGAGCCCCAAGCCGCCCAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
14: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACGGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATTCGGAGCCCCAAGCCGCCCAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
15: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACGGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATCCGGAGCCCCAGGCCGCCCAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
16: CCAGGGAGAGCGGGGCAGCGCACGGCTGGTGACAGGCTCAGCTCTGCACGGTGCAGAGGGAGGATCAGGGGCCACTGTTACCTCTGCAGTCGCTGCTGCCCATCCGGAGCCCCAAGCCGCCAAGGATGGTCTCGGACTGGCCGTCGCTGTACAGGAAGGCCGTGTCTATC
17: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTGTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTTACTAGTGAATGAATCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
18: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTCTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTAACTAGTGAGTGAGTCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
19: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTCTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTTACTAGTGAATGAGTCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
20: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTGTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTAACTAGTGAGTGAATCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
21: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTCTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTAACTAGTGAATGAATCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
22: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTCTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTAACTAGTGAATGAATCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
23: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTCTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTAACTAGTGAATGAATCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
24: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTCTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTAACTAGTGAATGAATCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
25: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTCTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTTACTAGTGAGTGAGTCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
26: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTGTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTAACTAGTGAGTGAGTCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
27: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTGTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTTACTAGTGAATGAGTCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
28: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTGTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTTACTAGTGAGTGAATCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
29: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTGTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTAACTAGTGAATGAATCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
30: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTCTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTTACTAGTGAATGAATCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
31: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTCTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTAACTAGTGAGTGAATCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
32: TGCCCCTCTCTTGTTCATTTGCCACCACTACTATGTAAGGCATTGCCTCACTACTCTGTCTCTCATCCCTATTCATACCTGTAGTCCTTATCACCATTTAACTAGTGAATGAGTCTGTTTCAGAGTCCCATCCTGTGTTTCTGATCTCTAGGACCAATCTCAGTGTCCAT
sequence
你知道如何在 R 中执行此操作吗？
谢谢
我只使用了前两行和感兴趣的列。我还减小了 refseq 的大小并使用 snp_position=2 以获得更好的可视化效果。但是，只要列名相同，它就会对您的完整数据同样有效。
输入：
df <- data.frame(alt=c("G","A"),snp_position=c(2,2),refseq=c("CCAGGGAGAGCGGGGCAGCGC",
"TCAGGGAGAGCGGGGCAGCGC"))
函数：
seq_mut <- function(refseq,snp_position,Mutated_allele){
combinations <- c("A","T","C","G")
WT_allele <- substr(refseq, snp_position, snp_position)
combinations <- combinations[combinations!=WT_allele]
refseq2 <- refseq
substr(refseq2, snp_position, snp_position) <- Mutated_allele
combinations <- combinations[combinations!=Mutated_allele]
seq <- refseq2
for(variant in combinations){
refseq2 <- refseq
substr(refseq2, snp_position, snp_position) <- variant
seq <- paste0(seq,";",refseq2)
}
return(seq)
}
与 dplyr:
library(dplyr)
df <- df %>% rowwise() %>% mutate(ref_seq_mut=seq_mut(refseq,snp_position,alt))
整理师：
library(tidyr)
df <- df %>% separate(ref_seq_mut,into=c("V1","V2","V3"))%>%
pivot_longer(cols=refseq:V3,values_to="refseq") %>% select(-name)
输出：
alt snp_position refseq
<chr> <dbl> <chr>
1 G 2 CCAGGGAGAGCGGGGCAGCGC
2 G 2 CGAGGGAGAGCGGGGCAGCGC
3 G 2 CAAGGGAGAGCGGGGCAGCGC
4 G 2 CTAGGGAGAGCGGGGCAGCGC
5 A 2 TCAGGGAGAGCGGGGCAGCGC
6 A 2 TAAGGGAGAGCGGGGCAGCGC
7 A 2 TTAGGGAGAGCGGGGCAGCGC
8 A 2 TGAGGGAGAGCGGGGCAGCGC
这是一个使用简化示例输入数据的选项。很多步骤说的太详细了，尽量运行一点一点的了解每个功能吧。
基本上，我在 refseq 上进行拆分，然后将 refseq 拆分为字母，然后使用 更新位置组合alt，然后粘贴回去。
df <- data.frame(alt = c("A","B", "C", "D", "E"),
snp_position = c(2, 4, 1, 3, 5),
refseq = c("-----", "-----",
"=====", "=====", "====="),
stringsAsFactors = FALSE)
res <- stack(
lapply(split(df, df$refseq), function(i){
s <- strsplit(i$refseq[ 1 ], "")[[ 1 ]]
pos <- i$snp_position
alt <- i$alt
unlist(
lapply(seq(nrow(i)), function(j)
combn(pos, j,
FUN = function(k){
res <- s
res[ k ] <- alt[ which(pos %in% k) ]
paste(res, collapse = "")
}))
)
}))
colnames(res) <- c("sequence", "refseq")
res
# sequence refseq
# 1 -A--- -----
# 2 ---B- -----
# 3 -A-B- -----
# 4 C==== =====
# 5 ==D== =====
# 6 ====E =====
# 7 C=D== =====
# 8 C===E =====
# 9 ==D=E =====
# 10 C=D=E =====