Davide
Reputation: 11
Get all combinations of multiple characters substitution at specific positions within a string
I have a data.table like this one below that contains groups of DNA strings (ref_seq column) and a series of mutations (characters within the alt column) with their relative location along the strings (snp_position column).
Because for n mutations, the resulting number of strings is 2^n, what I would like to do is to make a general function that allows to generate all the combinations of the alt characters replaced at the snp_position within the ref_seq string, while (preferably) keeping this data.frame structure
> 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>)
Desired output
> 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
do you know how to do this in R?
Thanks
Upvotes: 0
Views: 143
Answers (2)
zx8754
Reputation: 56149
Here is an option using simplified example input data. A lot of steps to go into too much detail, try to run it bit by bit to understand each function.
Basically, I am splitting on refseq, then splitting refseq into letters, then update combinations of positions with alt, then pasting back together.
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 =====
Upvotes: 0
Flo
Reputation: 41
I've used only the two first rows and the columns of interest. I've aslo reduced the size of the refseq and used snp_position=2 for better visualization. However, it will work the same with your full data as soon as the colnames are the same.
input:
df <- data.frame(alt=c("G","A"),snp_position=c(2,2),refseq=c("CCAGGGAGAGCGGGGCAGCGC",
"TCAGGGAGAGCGGGGCAGCGC"))
function:
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)
}
with dplyr:
library(dplyr)
df <- df %>% rowwise() %>% mutate(ref_seq_mut=seq_mut(refseq,snp_position,alt))
tidyr:
library(tidyr)
df <- df %>% separate(ref_seq_mut,into=c("V1","V2","V3"))%>%
pivot_longer(cols=refseq:V3,values_to="refseq") %>% select(-name)
output:
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
Upvotes: 1
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