通过成对对齐 R 中的多个文件 Alignment

Question

I have 15 protein sequences as fasta format in one file. I have to pairwise align them globally and locally then generate a distance score matrix 15x15 to construct dendrogram.

But when I do, ie A sequence is not aligning with itself and I get NA result. Moreover, AxB gives 12131 score but BxA gives NA. Thus R can not construct phylogenetic tree.

What should I do?

I'm using this script for the loop but it reads one way only:

for (i in 1:150) { 
  globalpwa<-pairwiseAlignment(toString(ProtDF[D[1,i],2]) 
                              ,toString(ProtDF[D[2,i],2]),
                              substitutionMatrix = "BLOSUM62",
                              gapOpening = 0,
                              gapExtension = -2,
                              scoreOnly=FALSE,
                              type="global")
  ScoreX[i]<-c(globalpwa@score)   
  nameSeq1[i]<-c(as.character(ProtDF[D[1,i],1]))
  nameSeq2[i]<-c(as.character(ProtDF[D[2,i],1]))
}

Answer 1

I used an example fasta file, protein sequence of RPS29 in fungi.

ProtDF <-
c(OQS54945.1 = "MINDLKVRKDVEKSKAHCHVKPFGKGSRACERCASHRGHNRKYGMNLCRRCLHTNAKILGFTSFD", 
XP_031008245.1 = "KHTESPVEPARRDNLKTAIMSHESVWNSRPRTYGKGARACRVCTHKAGLIRKYGLNICRQCFREKASDIGFVKVCDGHTDSSYDGSEF", 
TVY80688.1 = "MSHESVWNSRPRTYGKGARACRVCTHKAGLIRKYGLNICRQCFREKAADIGFVKHR", 
TVY57447.1 = "LPFLKIRVEPARRDNLKPAIMSHESVWNSRPRTYGKGARACRVCTHKAGLIRKYGLNICRQCFREKASDIGFVKVCVDAMGTLEPRASSPEL", 
TVY47820.1 = "EPARRDNLKTTIMSHESVWNSRPRTYGKGARACRVCTHKAGLIRKYGLNICRQCFREKAADIGFVK", 
TVY37154.1 = "AISKLNSRPQRPISTTPRKAKHTKSLVEPARRDNLKTAIMSHESVWNSRPRTYGKGARACRVCTHKAGLIRKYGLNICRQCFREKASDIGFVKHR", 
TVY29458.1 = "KHTESPVEPARRDNLKTAIMSHESVWNSRPRTYGKGARACRVCTHKAGLIRKYGLNICRQCFREKASDIGFVKVCDGHTDSSYDGSEF", 
TVY14147.1 = "MSHESVWNSRPRTYGKGARACRVCTHKAGLIRKYGLNICRQCFREKASDIGFVKVCDGWIGTLEL", 
`sp|Q6CPG3.1|RS29_KLULA` = "MAHENVWYSHPRKFGKGSRQCRISGSHSGLIRKYGLNIDRQSFREKANDIGFYKYR", 
`sp|Q8SS73.1|RS29_ENCCU` = "MSFEPSGPHSHRKPFGKGSRSCVSCYTFRGIIRKLMMCRRCFREYAGDIGFAIYD", 
`sp|O74329.3|RS29_SCHPO` = "MAHENVWFSHPRKYGKGSRQCAHTGRRLGLIRKYGLNISRQSFREYANDIGFVKYR", 
TPX23066.1 = "MTHESVFYSRPRNYGKGSRQCRVCAHKAGLIRKYGLLVCRQCFREKSQDIGFVKYR", 
`sp|Q6FWE3.1|RS29_CANGA` = "MAHENVWFSHPRRFGKGSRQCRVCSSHTGLIRKYDLNICRQCFRERASDIGFNKYR", 
`sp|Q6BY86.1|RS29_DEBHA` = "MAHESVWFSHPRNFGKGSRQCRVCSSHSGLIRKYDLNICRQCFRERASDIGFNKFR", 
XP_028490553.1 = "MSHESVWNSRPRSYGKGSRSCRVCKHSAGLIRKYDLNLCRQCFREKAKDIGFNKFR"
)

So you got it right to use combn. As you said, you need a distance score matrix for dendrogram, so better to store the values in a matrix. See below, I simply named the matrix after the names of the fasta, and slot in the pairwise values

library(Biostrings)
# you can also read in your file
# like ProtDF = readAAStringSet("fasta")

ProtDF=AAStringSet(ProtDF)

# combination like you want
# here we just use the names
D = combn(names(ProtDF),2)

#make the pairwise matrix
mat = matrix(NA,ncol=length(ProtDF),nrow=length(ProtDF))
rownames(mat) = names(ProtDF)
colnames(mat) = names(ProtDF)

# loop through D

for(idx in 1:ncol(D)){
       i <- D[1,idx]
       j <- D[2,idx]
       globalpwa<-pairwiseAlignment(ProtDF[i], 
                                    ProtDF[j],
                              substitutionMatrix = "BLOSUM62",
                              gapOpening = 0,
                              gapExtension = -2,
                              scoreOnly=FALSE,
                              type="global")
       mat[i,j]<-globalpwa@score
       mat[j,i]<-globalpwa@score
}

# if you need to make diagonal zero
diag(mat) <- 0

# plot
plot(hclust(as.dist(mat)))

Answer 2

An alternate method, if you're interested, using the same example as above:

library(DECIPHER)

ProtDF <- c(OQS54945.1 = "MINDLKVRKDVEKSKAHCHVKPFGKGSRACERCASHRGHNRKYGMNLCRRCLHTNAKILGFTSFD", 
            XP_031008245.1 = "KHTESPVEPARRDNLKTAIMSHESVWNSRPRTYGKGARACRVCTHKAGLIRKYGLNICRQCFREKASDIGFVKVCDGHTDSSYDGSEF", 
            TVY80688.1 = "MSHESVWNSRPRTYGKGARACRVCTHKAGLIRKYGLNICRQCFREKAADIGFVKHR", 
            TVY57447.1 = "LPFLKIRVEPARRDNLKPAIMSHESVWNSRPRTYGKGARACRVCTHKAGLIRKYGLNICRQCFREKASDIGFVKVCVDAMGTLEPRASSPEL", 
            TVY47820.1 = "EPARRDNLKTTIMSHESVWNSRPRTYGKGARACRVCTHKAGLIRKYGLNICRQCFREKAADIGFVK", 
            TVY37154.1 = "AISKLNSRPQRPISTTPRKAKHTKSLVEPARRDNLKTAIMSHESVWNSRPRTYGKGARACRVCTHKAGLIRKYGLNICRQCFREKASDIGFVKHR", 
            TVY29458.1 = "KHTESPVEPARRDNLKTAIMSHESVWNSRPRTYGKGARACRVCTHKAGLIRKYGLNICRQCFREKASDIGFVKVCDGHTDSSYDGSEF", 
            TVY14147.1 = "MSHESVWNSRPRTYGKGARACRVCTHKAGLIRKYGLNICRQCFREKASDIGFVKVCDGWIGTLEL", 
            `sp|Q6CPG3.1|RS29_KLULA` = "MAHENVWYSHPRKFGKGSRQCRISGSHSGLIRKYGLNIDRQSFREKANDIGFYKYR", 
            `sp|Q8SS73.1|RS29_ENCCU` = "MSFEPSGPHSHRKPFGKGSRSCVSCYTFRGIIRKLMMCRRCFREYAGDIGFAIYD", 
            `sp|O74329.3|RS29_SCHPO` = "MAHENVWFSHPRKYGKGSRQCAHTGRRLGLIRKYGLNISRQSFREYANDIGFVKYR", 
            TPX23066.1 = "MTHESVFYSRPRNYGKGSRQCRVCAHKAGLIRKYGLLVCRQCFREKSQDIGFVKYR", 
            `sp|Q6FWE3.1|RS29_CANGA` = "MAHENVWFSHPRRFGKGSRQCRVCSSHTGLIRKYDLNICRQCFRERASDIGFNKYR", 
            `sp|Q6BY86.1|RS29_DEBHA` = "MAHESVWFSHPRNFGKGSRQCRVCSSHSGLIRKYDLNICRQCFRERASDIGFNKFR", 
            XP_028490553.1 = "MSHESVWNSRPRSYGKGSRSCRVCKHSAGLIRKYDLNLCRQCFREKAKDIGFNKFR")

# All pairwise alignments:

# Convert characters to an AA String Set
ProtDF <- AAStringSet(ProtDF)

# Initialize some outputs
AliMat <- matrix(data = list(),
                 ncol = length(ProtDF),
                 nrow = length(ProtDF))

DistMat <- matrix(data = 0,
                  ncol = length(ProtDF),
                  nrow = length(ProtDF))

# loop through the upper triangle of your matrix
for (m1 in seq_len(length(ProtDF) - 1L)) {
  for (m2 in (m1 + 1L):length(ProtDF)) {
    # Align each pair
    AliMat[[m1, m2]] <- AlignSeqs(myXStringSet = ProtDF[c(m1, m2)],
                                  verbose = FALSE)

    # Assign a distance to each alignment, fill both triangles of the matrix
    DistMat[m1, m2] <- DistMat[m2, m1] <- DistanceMatrix(myXStringSet = AliMat[[m1, m2]],
                                                         type = "dist", # return a single value
                                                         includeTerminalGaps = TRUE, # return a global distance
                                                         verbose = FALSE)
  }
}

dimnames(DistMat) <- list(names(ProtDF),
                          names(ProtDF))

Dend01 <- IdClusters(myDistMatrix = DistMat,
                     method = "NJ",
                     type = "dendrogram",
                     showPlot = FALSE,
                     verbose = FALSE)

# A single multiple alignment:

AllAli <- AlignSeqs(myXStringSet = ProtDF,
                    verbose = FALSE)

AllDist <- DistanceMatrix(myXStringSet = AllAli,
                          type = "matrix",
                          verbose = FALSE,
                          includeTerminalGaps = TRUE)

Dend02 <- IdClusters(myDistMatrix = AllDist,
                     method = "NJ",
                     type = "dendrogram",
                     showPlot = FALSE,
                     verbose = FALSE)

Dend01, from all the pairwise alignments:

Dend02, from a single multiple alignment:

Finally, DECIPHER has a function for loading up your alignment in your browser just to look at it, which, if your alignments are huge, can be a bit of a mistake, but in this case (and in cases up to a few hundred short sequences) is just fine:

BrowseSeqs(AllAli)

A side note about BrowseSeqs, for some reason it doesn't behave well with Safari, but it plays just fine with Chrome. Sequences are displayed in the order in which they exist in the aligned string set.

EDIT: BrowseSeqs DOES play fine with safari directly, but it does have a weird issue with being incorporated with HTMLs knitted together with RMarkdown. Weird, but not applicable here.

Another big aside: All of the functions i've used have a processors argument, which is set to 1 by default, if you'd like to get greedy with your cores you can set it to NULL and it'll just grab everything available. If you're aligning very large string sets, this can be pretty useful, if you're doing trivially small things like this example, not so much.

combn is a great function and I use it all the time. However for these really simple set ups I like looping through the upper triangle, but that's just a personal preference.