Gapped BLAST and PSI-BLAST

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Gapped BLAST and PSI-BLAST

• Altschul et al
• Presenter ??? ???

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Outline

• BLAST 1.0 background (from lecture slides)
• BLAST 2.0
• Gapped BLAST
• PSI-BLAST
• Demonstration

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Statistical preliminaries

• Pi background probability that amino acids
  occur randomly at all position
• E number of distinct HSPs with normalized score
  at least S
• sij
• qij target frequency of aligned pair of letters
  (i, j) with HSP, high-scoring segment paris

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Outline

• BLAST 1.0 background (from lecture slides)
• BLAST 2.0
• Gapped BLAST
• PSI-BLAST

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BLAST

• Basic Local Alignment Search Tool(by Altschul,
  Gish, Miller, Myers and Lipman)
• The central idea of the BLAST algorithm is that a
  statistically significant alignment is likely to
  contain a high-scoring pair of aligned words.

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The maximal segment pair measure

• A maximal segment pair (MSP) is defined to be the
  highest scoring pair of identical length segments
  chosen from 2 sequences.(for DNA Identities
  5 Mismatches -4)

• The MSP score may be computed in time
  proportional to the product of their lengths.
  (How?) An exact procedure is too time consuming.
• BLAST heuristically attempts to calculate the MSP
  score.

the highest scoring pair
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BLAST

• Build the hash table for Sequence A.
• Scan Sequence B for hits.
• Extend hits.

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BLAST
Step 1 Build the hash table for Sequence A.
(3-tuple example)
For protein sequences Seq. A ELVISAdd xyz to
the hash table if Score(xyz, ELV) ? TAdd
xyz to the hash table if Score(xyz, LVI) ?
TAdd xyz to the hash table if Score(xyz,
VIS) ? T
For DNA sequences Seq. A AGATCGAT
12345678 AAAAAC..AGA 1..ATC 3..CGA
5..GAT 2 6..TCG 4..TTT

The higher T, the less sensitivity, but faster
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BLAST
Step2 Scan sequence B for hits.
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BLAST
Step2 Scan sequence B for hits.
Step 3 Extend hits.
BLAST 2.0 saves the time spent in extension, and
considers gapped alignments.
hit
Terminate if the score of the sxtension fades
away. (That is, when we reach a segment pair
whose score falls a certain distance below the
best score found for shorter extensions.)
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Outline

• BLAST 1.0 background (from lecture slides)
• BLAST 2.0
• Gapped BLAST
• PSI-BLAST

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Two-Hit Method

• BLAST 1.o
• Extension step accounts for 90 of total time
• Observations
• HSP of interest is much longer than a single word
  pair
• Entail multiple hits on the same diagonal and
  within short distance of one another
• Invoke an extension only when two non-overlapping
  hits are found within distance A on the same
  diagonal

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Demonstration

• Recenti the most recent hit found on the ith
  diagonal (always increasing)

overlap
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Discussion

• T must to be lowered
• More one-hits while the majority are dismissed
• Speed
• Twice as rapid as one-hit
• Sensitivity
• Almost the same

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Outline

• BLAST 1.0 background (from lecture slides)
• BLAST 2.0
• Gapped BLAST
• PSI-BLAST

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Gapped BLAST

• Original BLAST find several distinct HSPs
• All HSPs related to one alignment should be found
  
• Now
• Find one HSP only seed, than use 2-hit
• T can be raised ? faster
• Find all HSPs vs find one HSP for one optimal
  alignment
• For example, result should gt 0.95, p miss prob
  of HSP
• Orignial with 2 HSP (1-p)(1-p)gt0.95? plt0.025
• Now p2lt0.05?p0.22

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Gapped BLAST (contd)

• A gapped extension takes much longer to execute
  than an ungapped extension, but by performing
  very few of them the fraction of the total time
  could be kept low.
• Trigger a gapped extension for any HSP exceeding
  score Sg

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Example

• Original BLAST locates only the first and the
  last ungapped aligment, E-value gt 50 times

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Outline

• BLAST 1.0 background (from lecture slides)
• BLAST 2.0
• Gapped BLAST
• PSI-BLAST

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PSI-BLAST

• position-specific score matrices
• Vs substitution matrices
• Use it as ordinary ways
• Iterated, using position-specific score matrices
• For a BLAST run
• Constructed automatically from the output
• Use this matrix in place of the query for the
  next run
• For proteins, query L
• Position-specific matrix L 20
• Benefits
• Better to detect weak relationships

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Construct Position-specific matrix

• Construct multiple alignment M from the output
• For every column of M
• Find reduced Mc of column C
• Calculate scores in column C of the
  position-specific matrix

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Construct multiple alignment M

• Collect sequence segments output
• With E-value below a Threshold (why)
• Identical sequence are dropped
• Pair-wise alignment columns with query involves
  inserted gap are ignored
• Multiple alignment M has same length (column
  length) as query

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Construct multiple alignment M
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Calculate position-specific matrix score

• The scores of a given alignment column should
  dependent the residues appeared on the column
• But upon those in other columns as well

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Find reduced Mc of column C

• R sequences contribute a residue in column C
• Mc those columns of M in which all the sequences
  are represented

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Calculate scores in column C of the
position-specific matrix

• Related to all residues frequency observed fi,
  and number of independent residues in column C
  (Nc)
• log(Qi/Pi)
• Qi estimated probability for residue i to be
  found in C

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BLAST applied to position-specific matrices

• Scale with sij

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• Thank you
• Any problems now?

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Outline

• BLAST 1.0 background (from lecture slides)
• BLAST 2.0
• Gapped BLAST
• PSI-BLAST
• Demonstration