Gapped BLAST and PSI-BLAST

Altschul et alPresenter: 張耿豪 莊凱翔

Outline

BLAST 1.0 background (from lecture slides)

BLAST 2.0 Gapped BLAST PSI-BLAST Demonstration

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

Outline

BLAST 1.0 background (from lecture slides)

BLAST 2.0 Gapped BLAST PSI-BLAST

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.

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 highest scoring pair

•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.

BLAST

1) Build the hash table for Sequence A.2) Scan Sequence B for hits.3) Extend hits.

BLASTStep 1: Build the hash table for Sequence A. (3-tuple example)

For DNA sequences:

Seq. A = AGATCGAT 12345678AAAAAC..AGA 1..ATC 3..CGA 5..GAT 2 6..TCG 4..

TTT

For protein sequences:

Seq. A = ELVIS

Add xyz to the hash table if Score(xyz, ELV) ≧ T;Add xyz to the hash table if Score(xyz, LVI) ≧ T;Add xyz to the hash table if Score(xyz, VIS) ≧ T;

The higher T, the less sensitivity, but faster

BLASTStep2: Scan sequence B for hits.

BLASTStep2: Scan sequence B for hits.

Step 3: Extend hits.

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.)

BLAST 2.0 saves the time spent in extension, and

considers gapped alignments.

Outline

BLAST 1.0 background (from lecture slides)

BLAST 2.0 Gapped BLAST PSI-BLAST

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

Demonstration

Recent[i]: the most recent hit found on the ith diagonal (always increasing)

> A

overlap

< A Extend!

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

Outline

BLAST 1.0 background (from lecture slides)

BLAST 2.0 Gapped BLAST PSI-BLAST

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 > 0.95, p: miss prob of HSP Orignial with 2 HSP: (1-p)(1-p)>0.95 p<0.025 Now: p2<0.05p=0.22

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

Example

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

Outline

BLAST 1.0 background (from lecture slides)

BLAST 2.0 Gapped BLAST PSI-BLAST

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

Construct Position-specific matrix

1. Construct multiple alignment M from the output

2. For every column of M1) Find reduced Mc of column C

2) Calculate scores in column C of the position-specific matrix

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

Construct multiple alignment M

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

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

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

Thank you

Any problems now?

Outline

BLAST 1.0 background (from lecture slides)

BLAST 2.0 Gapped BLAST PSI-BLAST Demonstration