\chapter{Sequence alignment} \iffalse \begin{algorithm} \caption{Needleman-Wunsch Algorithm} \begin{algorithmic}[1] \Procedure{FillMatrix}{$S_{1}$: Array($m$), $S_{2}$: Array($n$)} \Comment{$sub(a, b)$ is the substitution score, $del(a)$ and $ins(a)$ are the deletion and insertion penalty, in regard with the reference $S_{1}$ sequence} \State $M = $ Array($m+1$, $n+1$) \Comment{Initialize the matrix first column and first row} \State $P = $ Array($m$, $n$) \Comment{Store the direction of the cell we chose to build the next cell up on.} \State $M[0][0] = 0$ \For {($i = 1$; $i < m+1$; $i++$)} \State $M[i][0] = M[i-1][0] + gap\_penalty$ \EndFor \For {($j = 1$; $j < n+1$; $j++$)} \State $M[0][j] = M[0][j-1] + gap\_penalty$ \EndFor \Comment{Fill the remaining matrix} \For {($i = 1$; $i < m+1$; $i++$)} \For {($j = 1$; $j < n+1$; $j++$)} \State $delete = M[i-1][j] + gap\_penalty$ \State $insert = M[i][j-1] + gap\_penalty$ \State $substitute = M[i-1][j-1] + sub(S_{1}[i-1], S_{2}[j-1])$ \State $choice = \min \{delete, insert, substitute\}$ \If {$substitute = choice$} \State $P[i-1][j-1] = '\nwarrow'$ \ElsIf {$deletion = choice$} \State $P[i-1][j-1] = '\leftarrow'$ \Else \State $P[i-1][j-1] = '\uparrow'$ \EndIf \State $M[i][j] = choice$ \EndFor \EndFor \EndProcedure \end{algorithmic} \end{algorithm} \begin{algorithm} \caption{Needleman-Wunsch Algorithm (Backtrack)} \begin{algorithmic}[1] \Procedure{ShowAlignment}{$S_{1}$: Array($m$), $S_{2}$: Array($n$)} \State $extend_{1} = ''$ \State $extend_{2} = ''$ \State $i = m$ \State $j = n$ \While{$i > 0$ and $j > 0$} \If {$P[i-1][j-1] = '\nwarrow'$} \State $extend_{1} = S_{1}[i-1] \circ extend_{1}$ \State $extend_{2} = S_{2}[j-1] \circ extend_{2}$ \State $i--$ \State $j--$ \ElsIf {$P[i-1][j-1] = '\uparrow'$} \State $extend_{1} = S_{1}[i-1] \circ extend_{1}$ \State $extend_{2} = '-' \circ extend_{2}$ \State $i--$ \Else \State $extend_{1} = '-' \circ extend_{1}$ \State $extend_{2} = S_{2}[j-1] \circ extend_{2}$ \State $j--$ \EndIf \EndWhile \While{$i > 0$} \State $extend_{1} = S_{1}[i-1] \circ extend_{1}$ \State $extend_{2} = '-' \circ extend_{2}$ \State $i--$ \State \Call{Insert}{0, $alignment$,$tuple$} \EndWhile \While{$j > 0$} \State $extend_{1} = '-' \circ extend_{1}$ \State $extend_{2} = S_{2}[j-1] \circ extend_{2}$ \State $j--$ \EndWhile \State \Call{print}{$extend_{1}$} \State \Call{print}{$extend_{2}$} \EndProcedure \State \Call{FillMatrix}{$S_{1}$, $S_{2}$} \State \Call{ShowAlignment}{$S_{1}$, $S_{2}$} \end{algorithmic} \end{algorithm} \fi \begin{algorithm} \caption{Needleman-Wunsch Algorithm, Build the matrix} \begin{algorithmic}[1] \Procedure{FillMatrix}{$S_{1}$: Array($m$), $S_{2}$: Array($n$)} \State $M = $ Array($m+1$, $n+1$) \State $P = $ Array($m$, $n$) \Comment{Store the direction of the cell we chose to build the next cell up on.} \State $M[0][0] = 0$ \For {($i = 1$; $i < m+1$; $i++$)} \State $M[i][0] = M[i-1][0] + gap\_penalty$ \EndFor \For {($j = 1$; $j < n+1$; $j++$)} \State $M[0][j] = M[0][j-1] + gap\_penalty$ \EndFor \For {($i = 1$; $i < m+1$; $i++$)} \For {($j = 1$; $j < n+1$; $j++$)} \State $delete = M[i-1][j] + gap\_penalty$ \State $insert = M[i][j-1] + gap\_penalty$ \State $substitute = M[i-1][j-1] + sub(S_{1}[i-1], S_{2}[j-1])$ \State $M[i][j] = \min \{substitute, insert, delete\}$ \EndFor \EndFor \EndProcedure \end{algorithmic} \end{algorithm} \begin{algorithm} \caption{Needleman-Wunsch Algorithm, reconstruct the alignment} \begin{algorithmic}[1] \Procedure{BacktrackAlignment}{$S_{1}$: Array($m$), $S_{2}$: Array($n$)} \State $alignment = LinkedList$ \State $i = m$ \State $j = n$ \While{$i > 0$ and $j > 0$} \If {$M[i-1][j-1] = M[i][j] - sub(S_{1}[i-1], S_{2}[j-1])$} \State $tuple = \begin{pmatrix} S_{1}[i-1] \\ S_{2}[j-1] \end{pmatrix}$ \State $i--$ \State $j--$ \ElsIf {$M[i-1][j-1] = M[i][j-1] - gap\_penalty$} \State $tuple = \begin{pmatrix} S_{1}[i-1] \\ \varepsilon \end{pmatrix}$ \State $i--$ \Else \State $tuple = \begin{pmatrix} \varepsilon \\ S_{2}[j-1] \end{pmatrix}$ \State $j--$ \EndIf \State \Call{Insert}{0, $alignment$,$tuple$} \EndWhile \While{$i > 0$} \State $tuple = \begin{pmatrix} S_{1}[i-1] \\ \varepsilon \end{pmatrix}$ \State $i--$ \State \Call{Insert}{0, $alignment$,$tuple$} \EndWhile \While{$j > 0$} \State $tuple = \begin{pmatrix} \varepsilon \\ S_{2}[j-1] \end{pmatrix}$ \State $j--$ \State \Call{Insert}{0, $alignment$,$tuple$} \EndWhile \EndProcedure \State \Call{FillMatrix}{$S_{1}$, $S_{2}$} \State \Call{BacktrackAlignment}{$S_{1}$, $S_{2}$} \end{algorithmic} \end{algorithm} \begin{algorithm} \caption{Backtrack a single alignment in a recursive way} \begin{algorithmic}[1] \State $S_{1}$: Array($m$), $S_{2}$: Array($n$), $M$: Array($m+1$, $n+1$), \Function{BacktrackRecurse}{$i$, $j$} \If {$i > 0$ and $j > 0$} \If {$M[i-1][j-1] = M[i][j] - sub(S_{1}[i-1], S_{2}[j-1])$} \State $z = $ \Call{BacktrackRecurse}{$S_{1}$, $S_{2}$, $M$, $i-1$, $j-1$} \State $z = \begin{pmatrix} S_{1}[i-1] \\ S_{2}[j-1] \end{pmatrix} \circ z$ \ElsIf {$M[i-1][j] + gap\_penalty = M[i][j]$} \State $z = $ \Call{BacktrackRecurse}{$S_{1}$, $S_{2}$, $M$, $i-1$, $j$} \State $z = \begin{pmatrix} S_{1}[i-1] \\ \varepsilon \end{pmatrix} \circ z$ \Else \State $z = $ \Call{BacktrackRecurse}{$S_{1}$, $S_{2}$, $M$, $i$, $j-1$} \State $z = \begin{pmatrix} \varepsilon \\ S_{2}[j-1] \end{pmatrix} \circ z$ \EndIf \ElsIf {$i > 0$} \State $z = $ \Call{BacktrackRecurse}{$S_{1}$, $S_{2}$, $M$, $i-1$, $j$} \State $z = \begin{pmatrix} S_{1}[i-1] \\ \varepsilon \end{pmatrix} \circ z$ \ElsIf {$j > 0$} \State $z = $ \Call{BacktrackRecurse}{$S_{1}$, $S_{2}$, $M$, $i$, $j-1$} \State $z = \begin{pmatrix} \varepsilon \\ S_{2}[j-1] \end{pmatrix} \circ z$ \Else \State \Return [] \EndIf \Else \State \Return $z$ \EndIf \EndFunction \Function{Backtrack}{$S_{1}$: Array($m$), $S_{2}$: Array($n$), $M$: Array($m+1$, $n+1$)} \State \Return \Call{BacktrackRecurse}{$S_{1}$, $S_{2}$, $M$, $m$, $n$} \EndFunction \end{algorithmic} \end{algorithm} \begin{algorithm} \caption{Backtrack all the optimum alignments in a recursive way} \begin{algorithmic}[1] \Procedure{BacktrackRecurse}{$S_{1}$: Array($m$), $S_{2}$: Array($n$), $M$: Array($m+1$, $n+1$), $i$, $j$} \If {$i > 0$ and $j > 0$} \If {$M[i-1][j-1] = M[i][j] - sub(S_{1}[i-1], S_{2}[j-1])$} \State $value = \begin{pmatrix} S_{1}[i-1] \\ S_{2}[j-1] \end{pmatrix}$ \State $z' = value \circ z$ \State \Call{BacktrackRecurse}{$S_{1}$, $S_{2}$, $M$, $i-1$, $j-1$, $z'$} \EndIf \If {$M[i-1][j] + gap\_penalty = M[i][j]$} \State $value = \begin{pmatrix} S_{1}[i-1] \\ \varepsilon \end{pmatrix}$ \State $z' = value \circ z$ \State \Call{BacktrackRecurse}{$S_{1}$, $S_{2}$, $M$, $i-1$, $j$, $z'$} \EndIf \If {$M[i][j-1] + gap\_penalty = M[i][j]$} \State $value = \begin{pmatrix} \varepsilon \\ S_{2}[j-1] \end{pmatrix}$ \State $z' = value \circ z$ \State \Call{BacktrackRecurse}{$S_{1}$, $S_{2}$, $M$, $i$, $j-1$, $z'$} \EndIf \ElsIf {$i > 0$} \State $value = \begin{pmatrix} S_{1}[i-1] \\ \varepsilon \end{pmatrix}$ \State $z' = value \circ z$ \State \Call{BacktrackRecurse}{$S_{1}$, $S_{2}$, $M$, $i-1$, $j$, $z'$} \ElsIf {$j > 0$} \State $value = \begin{pmatrix} \varepsilon \\ S_{2}[j-1] \end{pmatrix}$ \State $z' = value \circ z$ \State \Call{BacktrackRecurse}{$S_{1}$, $S_{2}$, $M$, $i$, $j-1$, $z'$} \Else \State \Call{print}{$z$} \EndIf \EndProcedure \Procedure{Backtrack}{$S_{1}$: Array($m$), $S_{2}$: Array($n$), $M$: Array($m+1$, $n+1$)} \State \Return \Call{BacktrackRecurse}{$S_{1}$, $S_{2}$, $M$, $m$, $n$, []} \EndProcedure \end{algorithmic} \end{algorithm} \begin{figure} \centering \includegraphics{figures/part2/needle.pdf} \caption{Needleman-Wunsch global alignment matrix with an example of optimal path.} \end{figure}