我想找到一个序列中有多少个基因组组合。我的意思是对于二进制组合:AA,AT,AG,AC ...等16种组合;或对于3元素组合ATG,ACG ... 64种组合。我知道如何用一个包装来做,我会在这里写下来。我想创建自己的代码来执行此操作
seqinr软件包非常适合其工作。那是我用来的代码;
install.packages('seqinr')
library(seqinr)
m = read.fasta(file='sequence.fasta')
mseq = m[[1]]
count(mseq,2) # gives how many binary combinations are found in the seq
count(mseq,3) # gives how many 3-elemented combinations are found in the seq
答案 0 :(得分:2)
这是一个很慢的方法。我敢肯定,在生物导体包装中速度更快。
# some practice data
mseq = paste(sample(c("A", "C", "G", "T"), 1000, rep=T), collapse="")
# define a function called count
count = function(mseq, n){
# split the sequence into every possible sub sequence of length n
x = sapply(1:(nchar(mseq) - n + 1), function(i) substr(mseq, i, i+n-1))
# how many unique sub sequences of length R are there?
length(table(x))
}
实际上只是检查了一下,这几乎就是他们的做法:
function (seq, wordsize, start = 0, by = 1, freq = FALSE, alphabet = s2c("acgt"),
frame = start)
{
if (!missing(frame))
start = frame
istarts <- seq(from = 1 + start, to = length(seq), by = by)
oligos <- seq[istarts]
oligos.levels <- levels(as.factor(words(wordsize, alphabet = alphabet)))
if (wordsize >= 2) {
for (i in 2:wordsize) {
oligos <- paste(oligos, seq[istarts + i - 1], sep = "")
}
}
counts <- table(factor(oligos, levels = oligos.levels))
if (freq == TRUE)
counts <- counts/sum(counts)
return(counts)
}
如果要查找函数的代码,请使用getAnywhere()
getAnywhere(count)
答案 1 :(得分:0)
简单的事情就是这样:
# Generate a test sequence
set.seed(1234)
testSeq <- paste(sample(LETTERS[1:3], 100, replace = T), collapse = "")
# Split string into chunks of size 2 and then count occurrences
testBigram <- substring(testSeq, seq(1, nchar(testSeq), 2), seq(2, nchar(testSeq), 2))
table(testBigram)
AA AB AC BA BB BC CA CB CC
10 10 14 3 3 2 2 5 1
这是使用“函数工厂”(https://adv-r.hadley.nz/function-factories.html)的一种方式。
2元素和3元素的组合是大小为2和3的n-gram。因此,我们将此n-gram函数工厂化。
# Generate a function to create a function
ngram <- function(size) {
function(myvector) {
substring(myvector, seq(1, nchar(myvector), size), seq(size, nchar(myvector), size))
}
}
# Assign the functions names (optional)
bigram <- ngram(2)
trigram <- ngram(3)
# 2 element combinations
table(bigram(testSeq))
AA AB AC BA BB BC CA CB CC
10 10 14 3 3 2 2 5 1
# count of 2 element combinations
length(unique(bigram(testSeq)))
[1] 9
# counting function
count <- function(mseq, n) length(unique(ngram(n)(mseq)))
count(testSeq, 2)
[1] 9
# and if we wanted to do with with 3 element combinations
table(trigram(testSeq))