The Needleman–Wunsch algorithm performs a global alignment on two sequences (called A and B here). It is commonly used in bioinformatics to align protein or nucleotide sequences. The Smith-Waterman algorithm is a well-known algorithm for performing local sequence alignment; that is, for determining similar regions between two nucleotide or protein sequences. Instead of looking at the total sequence, the Smith-Waterman algorithm compares segments of all possible lengths and optimizes the similarity measure.For the details, see the code as follow:
Needleman–Wunsch algorithm
public void NW(String f1, String f2) { //implement of Needleman–Wunsch algorithm;
int[][] score = new int[26][26]; //for the 26 English characters;
SimMatrix(score); //forming similarity matrix and store it in score;
String seq = "abcdeaghijklmnopqrstuvwxyz";//compare with the input string to form numbers;
int[] seq1 = new int[f1.length()];
int[] seq2 = new int[f2.length()];
int i;
int j;
for (i = 0; i < f1.length(); i++) { //changing the characters to the numbers
for (j = 0; j < seq.length(); j++) { //to read the score[][];
if (f1.charAt(i) == seq.charAt(j))
seq1[i] = j;
}
}
for (i = 0; i < f2.length(); i++) {
for (j = 0; j < seq.length(); j++) { //changing the characters to the numbers
if (f2.charAt(i) == seq.charAt(j)) //to read the score[][];
seq2[i] = j;
}
}
int gap = -5; //defining gap penalty;
int match, delete, insert;
int[][] F = new int[f1.length()+1][f2.length()+1]; //forming F[][];
for (j = 0; j <= f2.length(); j++) {
F[0][j] = gap * j;
}
for (i = 0; i <= f1.length(); i++) {
F[i][0] = gap * i;
}
for (i = 1; i <= f1.length(); i++) { //assigned the optimal score for the alignment;
for (j = 1; j <= f2.length(); j++) {
match = F[i - 1][j - 1] + score[seq1[i-1]][seq2[j-1]];
delete = F[i - 1][j] + gap;
insert = F[i][j - 1] + gap;
if ((match > delete) && (match > insert)) {
F[i][j] = match;
} else if (delete > insert) {
F[i][j] = delete;
} else {
F[i][j] = insert;
}
}
}
String Alignmentf1 = ""; //tracing back the pathway;
String Alignmentf2 = "";
i = f1.length();
j = f2.length();
while ((i > 0) && (j > 0)) {
int Score = F[i][j];
int ScoreDiag = F[i-1][j-1]; //do not have to define ScoreUp, it will not be used;
int ScoreLeft = F[i - 1][j];
if (Score == (ScoreDiag + score[seq1[i-1]][seq2[j-1]])) {
Alignmentf1 = f1.charAt(i-1) + Alignmentf1;
Alignmentf2 = f2.charAt(j-1) + Alignmentf2;
i = i - 1;
j = j - 1;
} else if (Score == ScoreLeft + gap) {
Alignmentf1 = f1.charAt(i-1) + Alignmentf1;
Alignmentf2 = "-" + Alignmentf2;
i = i - 1;
} else {
Alignmentf1 = "-" + Alignmentf1;
Alignmentf2 = f2.charAt(j-1) + Alignmentf2;
j = j - 1;
}
}
while (i > 0) {
Alignmentf1 = f1.charAt(i-1) + Alignmentf1;
Alignmentf2 = "-" + Alignmentf2;
i = i - 1;
}
while (j > 0) {
Alignmentf1 = "-" + Alignmentf1;
Alignmentf2 = f2.charAt(j-1) + Alignmentf2;
j = j - 1;
}
System.out.println("Global alignment score=" + F[f1.length()][f2.length()]);
System.out.println("Sequence1= "+Alignmentf1);
System.out.println("Sequence2= "+Alignmentf2);
}
public String readSequence(String file) { //read in the sequence from the text;
String seq = "";
String line = "";
try {
BufferedReader br = new BufferedReader(new FileReader(file));
while ((line = br.readLine()) != null) {
seq = seq + line;
}
} catch (FileNotFoundException e) {
e.printStackTrace();
} catch (IOException e) {
e.printStackTrace();
}
return seq;
}
Smith–Waterman algorithm
public void SW(String f1, String f2) {
int i, j, m;
int match, mismatch, delete, insert;
int w=2;
int gap=-1;
int[][] H = new int[f1.length() + 1][f2.length() + 1];
int max=0;
int line=0, colum=0;
for (j = 0; j <= f2.length(); j++) {
H[0][j] = 0;
}
for (i = 0; i <= f1.length(); i++) {
H[i][0] = 0;
}
for (i = 1; i <=f1.length(); i++) { // assigned the optimal score for the alignment;
for (j = 1; j <=f2.length(); j++) {
match = H[i - 1][j - 1] + w;
mismatch=H[i - 1][j - 1]+gap;
delete = H[i - 1][j] + gap;
insert = H[i][j - 1] + gap;
if (f1.charAt(i-1) == f2.charAt(j-1)) {
m = match;
} else {
m = mismatch;
}
if ((m > delete) && (m > insert) && (m > 0)) {
H[i][j] = m;
} else if ((delete > insert) && (delete > 0)) {
H[i][j] = delete;
} else if (insert > 0) {
H[i][j] = insert;
} else {
H[i][j] = 0;
}
}
}
System.out.println("The matrix H[][]:");
for(i=0;i<=f1.length();i++){
for(j=0;j<=f2.length();j++){
System.out.print(H[i][j]+" "); //show the H[][] matrix;
}
System.out.println();
}
String Alignmentf1 = ""; // tracing back the pathway;
String Alignmentf2 = "";
for(i=0;i<=f1.length();i++){
for(j=0;j<=f2.length();j++){
if(H[i][j]>max){
max=H[i][j];
line=i;
colum=j;
}
}
}
i = line;
j = colum;
while ((i > 0) && (j > 0)) {
int Score = H[i][j];
int ScoreDiag = H[i-1][j-1]; // do not have to define ScoreUp, it will not be used;
int ScoreLeft = H[i - 1][j];
if (f1.charAt(i-1) == f2.charAt(j-1)) {
w = 2;
} else {
w = -1;
}
if (Score == (ScoreDiag + w)) {
Alignmentf1 = f1.charAt(i-1) + Alignmentf1;
Alignmentf2 = f2.charAt(j-1) + Alignmentf2;
i = i - 1;
j = j - 1;
} else if (Score == ScoreLeft + w) {
Alignmentf1 = f1.charAt(i-1) + Alignmentf1;
Alignmentf2 = "-" + Alignmentf2;
i = i - 1;
} else {
Alignmentf1 = "-" + Alignmentf1;
Alignmentf2 = f2.charAt(j-1) + Alignmentf2;
j = j - 1;
}
}
while (i > 0) {
Alignmentf1 = f1.charAt(i-1) + Alignmentf1;
Alignmentf2 = "-" + Alignmentf2;
i = i - 1;
}
while (j > 0) {
Alignmentf1 = "-" + Alignmentf1;
Alignmentf2 = f2.charAt(j-1) + Alignmentf2;
j = j - 1;
}
System.out.println("Highest value in matrix H[][]=" + H[line][colum]);
System.out.print("The value is in line" +line+",");
System.out.println(" colum" +colum);
System.out.println("Sequence1= "+Alignmentf1);
System.out.println("Sequence2= "+Alignmentf2);
}
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