How to perform basic Multiple Sequence Alignments in R?

(I've tried asking this on BioStars, but for the slight chance that someone from text mining would think there is a better solution, I am also reposting this here)

The task I'm trying to achieve is to align several sequences.

I don't have a basic pattern to match to. All that I know is that the "True" pattern should be of length "30" and that the sequences I have had missing values introduced to them at random points.

Here is an example of such sequences, were on the left we see what is the real location of the missing values, and on the right we see the sequence that we will be able to observe.

My goal is to reconstruct the left column using only the sequences I've got on the right column (based on the fact that many of the letters in each position are the same)

                     Real_sequence           The_sequence_we_see
1   CGCAATACTAAC-AGCTGACTTACGCACCG CGCAATACTAACAGCTGACTTACGCACCG
2   CGCAATACTAGC-AGGTGACTTCC-CT-CG   CGCAATACTAGCAGGTGACTTCCCTCG
3   CGCAATGATCAC--GGTGGCTCCCGGTGCG  CGCAATGATCACGGTGGCTCCCGGTGCG
4   CGCAATACTAACCA-CTAACT--CGCTGCG   CGCAATACTAACCACTAACTCGCTGCG
5   CGCACGGGTAAGAACGTGA-TTACGCTCA开发者_如何学PythonG CGCACGGGTAAGAACGTGATTACGCTCAG
6   CGCTATACTAACAA-GTG-CTTAGGC-CTG   CGCTATACTAACAAGTGCTTAGGCCTG
7   CCCA-C-CTAA-ACGGTGACTTACGCTCCG   CCCACCTAAACGGTGACTTACGCTCCG

Here is an example code to reproduce the above example:

ATCG <- c("A","T","C","G")
set.seed(40)
original.seq <- sample(ATCG, 30, T)
seqS <- matrix(original.seq,200,30, T)
change.letters <- function(x, number.of.changes = 15, letters.to.change.with = ATCG) 
{
    number.of.changes <- sample(seq_len(number.of.changes), 1)
    new.letters <- sample(letters.to.change.with , number.of.changes, T)
    where.to.change.the.letters <- sample(seq_along(x) , number.of.changes, F)
    x[where.to.change.the.letters] <- new.letters
    return(x)
}
change.letters(original.seq)
insert.missing.values <- function(x) change.letters(x, 3, "-") 
insert.missing.values(original.seq)

seqS2 <- t(apply(seqS, 1, change.letters))
seqS3 <- t(apply(seqS2, 1, insert.missing.values))

seqS4 <- apply(seqS3,1, function(x) {paste(x, collapse = "")})
require(stringr)
# library(help=stringr)
all.seqS <- str_replace(seqS4,"-" , "")

# how do we allign this?
data.frame(Real_sequence = seqS4, The_sequence_we_see = all.seqS)

I understand that if all I had was a string and a pattern I would be able to use

library(Biostrings)
pairwiseAlignment(...)

But in the case I present we are dealing with many sequences to align to one another (instead of aligning them to one pattern).

Is there a known method for doing this in R?

Writing an alignment algorithm in R looks like a bad idea to me, but there is an R interface to the MUSCLE algorithm in the bio3d package (function seqaln()). Be aware of the fact that you have to install this algorithm first.

Alternatively, you can use any of the available algorithms (eg ClustalW, MAFFT, T-COFFEE) and import the multiple sequence alignemts in R using bioconductor functionality. See eg here..

Though this is quite an old thread, I do not want to miss the opportunity to mention that, since Bioconductor 3.1, there is a package 'msa' that implements interfaces to three different multiple sequence alignment algorithms: ClustalW, ClustalOmega, and MUSCLE. The package runs on all major platforms (Linux/Unix, Mac OS, and Windows) and is self-contained in the sense that you need not install any external software. More information can be found on http://www.bioinf.jku.at/software/msa/ and http://www.bioconductor.org/packages/release/bioc/html/msa.html.

You can perform multiple alignment in R with the DECIPHER package.

Following your example, it would look something like:

library(DECIPHER)
dna <- DNAStringSet(all.seqS)
aligned_DNA <- AlignSeqs(dna)

It is fast and at least as accurate as the other methods listed here (see the paper). I hope that helps!

You are looking for a global alignment algorithm on multiple sequences. Did you look at Wikipedia before asking ?

First learn what global alignment is, then look for multiple sequence alignment.

Wikipedia doesn't give a lot of details about algorithms, but this paper is better.