fasta
M.Ummul halilunnisa
M.Sc –Ist year
Pondicherry university.
Introduction:
-fasta was developed by Lipman and pearson in 1985.
-tool used align the sequences(protein & DNA)
-best to make protein protein comparison.
-blast (modified version)
Fasta = protein to protein
Tfasta = protein to DNA
Lfasta = identifies 1/more regions of similarity
Plfasta= presents a dot matrix plot of regions of sequence
similarity between 2 sequences
Expansions:
Derived from logic of the dot plot
 compute best diagonals from all frames of alignment
The method looks for exact matches between
words in query and test sequence
 DNA words are usually 6 nucleotides long
 protein words are 2 amino acids long
Idea ?
Howto do the sequence alignment usingfasta?
 Identify the common k-words between the sequences.
 Identify the best diagonals.
 Score the regions.
 Join the aligned regions.
 Optimal alignment.
1.Identify the common k words:
-word based search=k tups
-local alignment
-finds the matching words
-creates diagonal by dot plot
2.Identify the best diagonals:
Scoretheregions:
 Score the best regions using =init 1
 It tries to join high scoring diagonals
 Rescoring by PAM-250 matrix =init n
Jointhe alignedregions& make an optimal alignment:
Howto manuallydo the fastasearch?
Retrieve the
sequence
from uniprot
paste the
sequence in
fasta tool
Submit the
sequence
Blast vs Fasta
• Blast is much faster than Fasta.
• Blast is much more accurate than Fasta.
• For closely matched sequences Blast is very accurate and for dissimilar sequence Fasta
is better software.
• Blast can be modified according to the need but Fasta cannot be modified.
• Blast has to use Fasta input format to get the output data.
• Blast is much more versatile and widely used than Fasta.
Fasta

Fasta

  • 1.
    fasta M.Ummul halilunnisa M.Sc –Istyear Pondicherry university.
  • 2.
    Introduction: -fasta was developedby Lipman and pearson in 1985. -tool used align the sequences(protein & DNA) -best to make protein protein comparison. -blast (modified version)
  • 3.
    Fasta = proteinto protein Tfasta = protein to DNA Lfasta = identifies 1/more regions of similarity Plfasta= presents a dot matrix plot of regions of sequence similarity between 2 sequences Expansions:
  • 6.
    Derived from logicof the dot plot  compute best diagonals from all frames of alignment The method looks for exact matches between words in query and test sequence  DNA words are usually 6 nucleotides long  protein words are 2 amino acids long Idea ?
  • 7.
    Howto do thesequence alignment usingfasta?  Identify the common k-words between the sequences.  Identify the best diagonals.  Score the regions.  Join the aligned regions.  Optimal alignment.
  • 8.
    1.Identify the commonk words: -word based search=k tups -local alignment -finds the matching words -creates diagonal by dot plot
  • 10.
  • 11.
    Scoretheregions:  Score thebest regions using =init 1  It tries to join high scoring diagonals  Rescoring by PAM-250 matrix =init n
  • 12.
    Jointhe alignedregions& makean optimal alignment:
  • 13.
    Howto manuallydo thefastasearch? Retrieve the sequence from uniprot paste the sequence in fasta tool Submit the sequence
  • 20.
    Blast vs Fasta •Blast is much faster than Fasta. • Blast is much more accurate than Fasta. • For closely matched sequences Blast is very accurate and for dissimilar sequence Fasta is better software. • Blast can be modified according to the need but Fasta cannot be modified. • Blast has to use Fasta input format to get the output data. • Blast is much more versatile and widely used than Fasta.