#' Finds the optimal local nucleotide sequence aligment with Smith-Waterman algorithm and BLOSUM as score matrix.
#'
#' @param sequence1 First vector with characters indicating some protein sequence.
#' @param sequence2 Second vector with characters indicating some protein sequence.
#' @param gapPenalty A number indicating the gap penalty value.
#' @param blosumName Name of the BLOSUM matrix.
#' @return List containing the score, the resulting aligned sequences and the matrix of aligment.
#' @examples
#' localAligmentProteinSequence(c("P","A","W","H","E","A","E"), c("H","E","A","G","A","W","G","H","E","E"), 8, "BLOSUM50")
localAligmentProteinSequence <- function(sequence1, sequence2, gapPenalty, blosumName){
if(exists(blosumName) == FALSE)
return("BLOSUM matrix with that name isn't available")
BLOSUM <- get(blosumName)
if(gapPenalty > 0)
d = gapPenalty * -1
else
d = gapPenalty
matrix <- matrix(data = NA, nrow = length(sequence1) + 1, ncol = length(sequence2) + 1)
dimnames(matrix) <- list(c("-", sequence1), c("-", sequence2))
matrix[1,1] = 0 #prviot element e nula
# popolnuvanje na prva kolona
for(i in 2:nrow(matrix)){
matrix[i,1] = 0
}
# popolnuvanje na prv red
for(j in 2:ncol(matrix)){
matrix[1,j] = 0
}
highestScore <- 0 #najgolemiot najden score za da znaeme od kade da pocneme so backtracking
highestScoreI <- 0 #indeksot na redicata od kade treba da pocneme so backtracking
highestScoreJ <- 0 #indeksot na kolonata od kade treba da pocneme so backtracking
# presmetka na matricata
for(i in 2:nrow(matrix)){
for(j in 2:ncol(matrix)){
rowname <- rownames(matrix)[i]
colname <- colnames(matrix)[j]
match <- matrix[i-1, j-1] + BLOSUM[rowname, colname]
delete <- matrix[i-1,j] + d
insert <- matrix[i,j-1] + d
matrix[i,j] <- max(0, match, insert, delete)
if(matrix[i,j] > highestScore){
highestScore <- matrix[i,j]
highestScoreI <- i
highestScoreJ <- j
}
}
}
finalScore <- highestScore
# back track
newSequence1 <- ""
newSequence2 <- ""
i <- highestScoreI
j <- highestScoreJ
while(TRUE){
score <- matrix[i,j]
if(score == 0)
break
scoreDiag <- matrix[i-1,j-1]
scoreLeft <- matrix[i,j-1]
scoreUp <- matrix[i-1,j]
rowname <- rownames(matrix)[i]
colname <- colnames(matrix)[j]
if(score == scoreUp + d){
newSequence1 <- paste(rowname, newSequence1, sep = "")
newSequence2 <- paste("-", newSequence2, sep = "")
i <- i - 1
}
else if(score == scoreLeft + d){
newSequence1 <- paste("-", newSequence1, sep = "")
newSequence2 <- paste(colname, newSequence2, sep = "")
j <- j - 1
}
else{
newSequence1 <- paste(rowname, newSequence1, sep = "")
newSequence2 <- paste(colname, newSequence2, sep = "")
i <- i - 1
j <- j - 1
}
}
solution = list(score = finalScore, sequence1 = newSequence1, sequence2 = newSequence2, matrix = matrix)
return(solution)
}
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