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I understand that the first BLAST yields almost the same results as blastp. The second time the iterated blast generates different results as it uses different matrix based on our first result.

But I don't understand how exactly the second matrix is generated ?

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3 Answers 3

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Addition to previous answers:

PSI-BLAST is a sort of machine learning algorithm which uses the results of the first alignment (PSSM) to score the next iteration of alignment. I would recommend you to refer to the NCBI bookshelf page on PSI-BLAST.

PSI-BLAST adopts a scoring scheme (PSSM) that is built based on a given set of data (the aligned sequences), rather than using a generalized scoring matrix. This improvisation updates the prior knowledge of the homologs and helps to detect similar sequences that were otherwise undetectable. With iterations the PSSM keeps getting updated, thereby, making the BLAST more sensitive in finding homologs.

How PSSM is constructed:

If a position in the alignment is conserved (i.e same residue in many sequences), it receives a high score whereas a position with low conservation gets a low score.

Score is based on relative counts of a residue in a position. If you want to know the details see here.

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Hi ! Thanks. Please see the comments to gergana's answer. –  biogirl Mar 5 at 6:19
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Check the link that I mention in the answer. It has some examples too. –  WYSIWYG Mar 5 at 6:23
    
I read that this method is much more sensitive for detecting distant relationships. What does this mean ? How using PSSM improve its senstivity ? (Sorry for bugging you so much but am really excited to learn this new(for me!) stuff !) –  biogirl Mar 5 at 8:00
    
Thank you lots :) –  biogirl Mar 5 at 9:02
    
edited the answer. –  WYSIWYG Mar 5 at 9:15

PSI-BLAST is Position-Specific Iterated BLAST.

I'm probably out of my depth here, but my understanding is that the results of the first, essentially standard, BLAST search are used to create a multiple sequence alignment. This alignment is then converted to a Position Specific Scoring Matrix (PSSM). (The linked Wikipedia entry shows this for DNA sequences, but the principle is exactly the same for protein sequences.) This matrix can then be used as the probe for the next round of BLAST, and the results of that alignment can be used judiciously to improve the matrix, and so on until the results converge.

Here is a link to some slides by Stephen Altschul which go into lots of detail.

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From Russ Altman (Stanford University) lecture:

Blast takes as an input a sequence, it searches the database, and outputs a set of alignments (a top ranked alignment, followed by a second-top ranked, a third, and so on). Then you take the top scoring sequences (you might use the E-value as a cutoff) and you can create a position-specific scoring matrix (PSSM) based on the occurrences of amino acids in all the columns of these alignments. This is allowed, because there is a high chance that these sequences are homologous to the query sequence and thus looking at the amino acids would give you a good sense of the variability in position that is allowed in the initial query sequence. The next step is to re-search the database for more hits. So now instead of searching with a sequence, you are searching with a profile, and you get another set of hits. You can iterate a few times which would give you a much more sensitive search.

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Hi! Thank you so much. So each time we iterate , a new PSSM is formed ? –  biogirl Mar 5 at 6:15
    
I also do not understand the significane of using this type of blast instead of standard blast. What specific/new information can i get by doing this type of blasting ? When wud i use this type of blast ? –  biogirl Mar 5 at 6:17
    
Yes, each time you iterate a new PSSM is formed. You might want to use it if you would want to identify homologs that are undetectable by simple BLAST. –  Gergana Vandova Mar 5 at 18:52

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