1. Local alignment and BLAST
Usman Roshan
BNFO 601

2. Local alignment Global alignment may not find local similarities
Modification of Needleman-Wunsch yields the Smith-Watermn algorithm for local alignment
Useful in motif detection, database search, short read mapping

3. Local alignment Global alignment initialization:
Local alignment recurrence

4. Local alignment Global alignment recurrence:
Local alignment recurrence

5. Local alignment traceback
Let T(i,j) be the traceback matrices and m and n be length of input sequences.
Global alignment traceback:
Begin from T(m,n) and stop at T(0,0).
Local alignment traceback:
Find i*,j* such that T(i*,j*) is the maximum over all T(i,j).
Begin traceback from T(i*,j*) and stop when
T(i,j) <= 0.

6. BLAST Local pairwise alignment heuristic
Faster than standard pairwise alignment programs such as SSEARCH, but less sensitive.
Online server:

7. BLAST
Given a query q and a target sequence, find substrings of length k (k-mers) of score at least t --- also called hits. k is normally 3 to 5 for amino acids and 12 for nucleotides.
Extend each hit to a locally maximal segment. Terminate the extension when the reduction in score exceeds a pre-defined threshold
Report maximal segments above score S.

8. Finding k-mers quickly
Preprocess the database of sequences:
For each sequence in the database store all k-mers in hash-table.
This takes linear time
Query sequence:
For each k-mer in the query sequence look up the hash table of the target to see if it exists
Also takes linear time