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FASTA
Introduction
• The FASTA algorithm is a heuristic method for
string comparison.
• Developed by Lipman and Pearson in 1985
and further improved in 1988.
• It performs Local alignment of sequences
• It uses hash coding in which the sequence is
broken into small “words or K-tuples” of
specific sizes.
FASTA
• FASTA’s general strategy
– is to find the most significant diagonals in the dot-
plot or dynamic programming matrix.
– compute best diagonals from all frames of
alignment in a dot plot
2) Word method looks for exact matches
between words in query and test sequence
– hash tables (fast computer technique)
– DNA words are usually 6 bases
– protein words are 1 or 2 amino acids
– only searches for diagonals in region of word
matches = faster searching
Steps in FASTA Algorithm
Four steps:
1. Identify regions of similarity:
• Using the ktup parameter which specifies the size of
the word
• uses the word hits to identify potential matches
between the query sequence and database sequence
• Lesser the ktup value, more sensitive the search
• By default ktup is 2 for proteins and 4 or 6 for
nucleotides
• 10 best diagonal regions found based on #matches and
distance between matches
2. Rescore regions and identify best initial
regions
• PAM250 or other scoring matrix used for
rescoring the 10 diagonal regions identified in
step 1 to allow for conservative replacements
and runs of identities shorter than ktup
• For each of the best diagonal regions, identify
“initial region” that is best scoring sub region
Makes Longest Diagonal
3) after all diagonals found, tries to join
diagonals by adding gaps
4) computes alignments in regions of best
diagonals
FASTA Algorithm
FASTA Alignments
FASTA Results - Histogram
!!SEQUENCE_LIST 1.0
(Nucleotide) FASTA of: b2.seq from: 1 to: 693 December 9, 2002 14:02
TO: /u/browns02/Victor/Search-set/*.seq Sequences: 2,050 Symbols:
913,285 Word Size: 6
Searching with both strands of the query.
Scoring matrix: GenRunData:fastadna.cmp
Constant pamfactor used
Gap creation penalty: 16 Gap extension penalty: 4
Histogram Key:
Each histogram symbol represents 4 search set sequences
Each inset symbol represents 1 search set sequences
z-scores computed from opt scores
z-score obs exp
(=) (*)
< 20 0 0:
22 0 0:
24 3 0:=
26 2 0:=
28 5 0:==
30 11 3:*==
32 19 11:==*==
34 38 30:=======*==
36 58 61:===============*
38 79 100:==================== *
40 134 140:==================================*
42 167 171:==========================================*
44 205 189:===============================================*====
46 209 192:===============================================*=====
48 177 184:=============================================*
FASTA Results - List
The best scores are: init1 initn opt z-sc E(1018780)..
SW:PPI1_HUMAN Begin: 1 End: 269
! Q00169 homo sapiens (human). phosph... 1854 1854 1854 2249.3 1.8e-117
SW:PPI1_RABIT Begin: 1 End: 269
! P48738 oryctolagus cuniculus (rabbi... 1840 1840 1840 2232.4 1.6e-116
SW:PPI1_RAT Begin: 1 End: 270
! P16446 rattus norvegicus (rat). pho... 1543 1543 1837 2228.7 2.5e-116
SW:PPI1_MOUSE Begin: 1 End: 270
! P53810 mus musculus (mouse). phosph... 1542 1542 1836 2227.5 2.9e-116
SW:PPI2_HUMAN Begin: 1 End: 270
! P48739 homo sapiens (human). phosph... 1533 1533 1533 1861.0 7.7e-96
SPTREMBL_NEW:BAC25830 Begin: 1 End: 270
! Bac25830 mus musculus (mouse). 10, ... 1488 1488 1522 1847.6 4.2e-95
SP_TREMBL:Q8N5W1 Begin: 1 End: 268
! Q8n5w1 homo sapiens (human). simila... 1477 1477 1522 1847.6 4.3e-95
SW:PPI2_RAT Begin: 1 End: 269
! P53812 rattus norvegicus (rat). pho... 1482 1482 1516 1840.4 1.1e-94
FASTA Results - Alignment
SCORES Init1: 1515 Initn: 1565 Opt: 1687 z-score: 1158.1 E(): 2.3e-58
>>GB_IN3:DMU09374 (2038 nt)
initn: 1565 init1: 1515 opt: 1687 Z-score: 1158.1 expect(): 2.3e-58
66.2% identity in 875 nt overlap
(83-957:151-1022)
60 70 80 90 100 110
u39412.gb_pr CCCTTTGTGGCCGCCATGGACAATTCCGGGAAGGAAGCGGAGGCGATGGCGCTGTTGGCC
|| ||| | ||||| | ||| |||||
DMU09374 AGGCGGACATAAATCCTCGACATGGGTGACAACGAACAGAAGGCGCTCCAACTGATGGCC
130 140 150 160 170 180
120 130 140 150 160 170
u39412.gb_pr GAGGCGGAGCGCAAAGTGAAGAACTCGCAGTCCTTCTTCTCTGGCCTCTTTGGAGGCTCA
||||||||| || ||| | | || ||| | || || ||||| ||
DMU09374 GAGGCGGAGAAGAAGTTGACCCAGCAGAAGGGCTTTCTGGGATCGCTGTTCGGAGGGTCC
190 200 210 220 230 240
180 190 200 210 220 230
u39412.gb_pr TCCAAAATAGAGGAAGCATGCGAAATCTACGCCAGAGCAGCAAACATGTTCAAAATGGCC
||| | ||||| || ||| |||| | || | |||||||| || ||| ||
DMU09374 AACAAGGTGGAGGACGCCATCGAGTGCTACCAGCGGGCGGGCAACATGTTTAAGATGTCC
250 260 270 280 290 300
240 250 260 270 280 290
u39412.gb_pr AAAAACTGGAGTGCTGCTGGAAACGCGTTCTGCCAGGCTGCACAGCTGCACCTGCAGCTC
|||||||||| ||||| | |||||| |||| ||| || ||| || |
DMU09374 AAAAACTGGACAAAGGCTGGGGAGTGCTTCTGCGAGGCGGCAACTCTACACGCGCGGGCT
310 320 330 340 350 360

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Fasta : steps, features, algorithm, result etc.

  • 2. Introduction • The FASTA algorithm is a heuristic method for string comparison. • Developed by Lipman and Pearson in 1985 and further improved in 1988. • It performs Local alignment of sequences • It uses hash coding in which the sequence is broken into small “words or K-tuples” of specific sizes.
  • 3. FASTA • FASTA’s general strategy – is to find the most significant diagonals in the dot- plot or dynamic programming matrix. – compute best diagonals from all frames of alignment in a dot plot 2) Word method looks for exact matches between words in query and test sequence – hash tables (fast computer technique) – DNA words are usually 6 bases – protein words are 1 or 2 amino acids – only searches for diagonals in region of word matches = faster searching
  • 4. Steps in FASTA Algorithm Four steps: 1. Identify regions of similarity: • Using the ktup parameter which specifies the size of the word • uses the word hits to identify potential matches between the query sequence and database sequence • Lesser the ktup value, more sensitive the search • By default ktup is 2 for proteins and 4 or 6 for nucleotides • 10 best diagonal regions found based on #matches and distance between matches
  • 5. 2. Rescore regions and identify best initial regions • PAM250 or other scoring matrix used for rescoring the 10 diagonal regions identified in step 1 to allow for conservative replacements and runs of identities shorter than ktup • For each of the best diagonal regions, identify “initial region” that is best scoring sub region
  • 6. Makes Longest Diagonal 3) after all diagonals found, tries to join diagonals by adding gaps 4) computes alignments in regions of best diagonals
  • 9. FASTA Results - Histogram !!SEQUENCE_LIST 1.0 (Nucleotide) FASTA of: b2.seq from: 1 to: 693 December 9, 2002 14:02 TO: /u/browns02/Victor/Search-set/*.seq Sequences: 2,050 Symbols: 913,285 Word Size: 6 Searching with both strands of the query. Scoring matrix: GenRunData:fastadna.cmp Constant pamfactor used Gap creation penalty: 16 Gap extension penalty: 4 Histogram Key: Each histogram symbol represents 4 search set sequences Each inset symbol represents 1 search set sequences z-scores computed from opt scores z-score obs exp (=) (*) < 20 0 0: 22 0 0: 24 3 0:= 26 2 0:= 28 5 0:== 30 11 3:*== 32 19 11:==*== 34 38 30:=======*== 36 58 61:===============* 38 79 100:==================== * 40 134 140:==================================* 42 167 171:==========================================* 44 205 189:===============================================*==== 46 209 192:===============================================*===== 48 177 184:=============================================*
  • 10. FASTA Results - List The best scores are: init1 initn opt z-sc E(1018780).. SW:PPI1_HUMAN Begin: 1 End: 269 ! Q00169 homo sapiens (human). phosph... 1854 1854 1854 2249.3 1.8e-117 SW:PPI1_RABIT Begin: 1 End: 269 ! P48738 oryctolagus cuniculus (rabbi... 1840 1840 1840 2232.4 1.6e-116 SW:PPI1_RAT Begin: 1 End: 270 ! P16446 rattus norvegicus (rat). pho... 1543 1543 1837 2228.7 2.5e-116 SW:PPI1_MOUSE Begin: 1 End: 270 ! P53810 mus musculus (mouse). phosph... 1542 1542 1836 2227.5 2.9e-116 SW:PPI2_HUMAN Begin: 1 End: 270 ! P48739 homo sapiens (human). phosph... 1533 1533 1533 1861.0 7.7e-96 SPTREMBL_NEW:BAC25830 Begin: 1 End: 270 ! Bac25830 mus musculus (mouse). 10, ... 1488 1488 1522 1847.6 4.2e-95 SP_TREMBL:Q8N5W1 Begin: 1 End: 268 ! Q8n5w1 homo sapiens (human). simila... 1477 1477 1522 1847.6 4.3e-95 SW:PPI2_RAT Begin: 1 End: 269 ! P53812 rattus norvegicus (rat). pho... 1482 1482 1516 1840.4 1.1e-94
  • 11. FASTA Results - Alignment SCORES Init1: 1515 Initn: 1565 Opt: 1687 z-score: 1158.1 E(): 2.3e-58 >>GB_IN3:DMU09374 (2038 nt) initn: 1565 init1: 1515 opt: 1687 Z-score: 1158.1 expect(): 2.3e-58 66.2% identity in 875 nt overlap (83-957:151-1022) 60 70 80 90 100 110 u39412.gb_pr CCCTTTGTGGCCGCCATGGACAATTCCGGGAAGGAAGCGGAGGCGATGGCGCTGTTGGCC || ||| | ||||| | ||| ||||| DMU09374 AGGCGGACATAAATCCTCGACATGGGTGACAACGAACAGAAGGCGCTCCAACTGATGGCC 130 140 150 160 170 180 120 130 140 150 160 170 u39412.gb_pr GAGGCGGAGCGCAAAGTGAAGAACTCGCAGTCCTTCTTCTCTGGCCTCTTTGGAGGCTCA ||||||||| || ||| | | || ||| | || || ||||| || DMU09374 GAGGCGGAGAAGAAGTTGACCCAGCAGAAGGGCTTTCTGGGATCGCTGTTCGGAGGGTCC 190 200 210 220 230 240 180 190 200 210 220 230 u39412.gb_pr TCCAAAATAGAGGAAGCATGCGAAATCTACGCCAGAGCAGCAAACATGTTCAAAATGGCC ||| | ||||| || ||| |||| | || | |||||||| || ||| || DMU09374 AACAAGGTGGAGGACGCCATCGAGTGCTACCAGCGGGCGGGCAACATGTTTAAGATGTCC 250 260 270 280 290 300 240 250 260 270 280 290 u39412.gb_pr AAAAACTGGAGTGCTGCTGGAAACGCGTTCTGCCAGGCTGCACAGCTGCACCTGCAGCTC |||||||||| ||||| | |||||| |||| ||| || ||| || | DMU09374 AAAAACTGGACAAAGGCTGGGGAGTGCTTCTGCGAGGCGGCAACTCTACACGCGCGGGCT 310 320 330 340 350 360