Download Statistics and Database Searching in Bioinformatics: Lecture 7 - Prof. Christopher Bystrof and more Study notes Biology in PDF only on Docsity! Bioinformatics 1: lecture 7 Statistics for pairwise alignments Database searching using FASTA Database searching using BLAST NCBI/Seqlab exercises You have seen.... Dynamic programming: Global alignment Global/local alignment (no end gaps. 3 ways to do it.) Local alignment Linear gap penalty Affine gap penalty How many ways are there to do DP? Searching millions of sequences Given a protein or DNA sequence, we want to find all of the sequences in GenBank (over 17 million sequences!!) that have a good alignment score. Each alignment score should be the optimal score (or a close approximation). How do we do it? DNA or Protein search? •Advantages of searching DNA databases •Disadvantages •Advantages of searching protein sequences •Disadvantages Larger database. Does not assume a reading frame. Can find similarity in non-coding regions (introns, promotor regions). Can find frameshift mutations. Can find pseudogenes. Slower. Not as sensitive. Ignores selective pressure at the protein level. Faster. More sensitive. More biologically relevant. Not applicable to non-coding DNA (promotors, introns, etc) Searching using Dynamic Programming SSEARCH DP returns the optimal alignment, given the scoring function (usually affine gap local alignment) Smith & Waterman Relatively slow, but more sensitive, and more selective, than FASTA and BLAST Optimal. heuristic FASTA CDGGAALP CDEEDDLP Finding identity matches is very fast. If two k-tuples are separated by exactly the same amount in both sequence, draw a diagonal. A gapless alignment. k-tuples k=2 FASTA Find all gapless alignments Score them using BLOSUM, keep the best Connect them using simple affine gap. (gap ext.= 0) If this alignment one of the best scores in the database search, go back and realign using DP. BLAST ~50 high-scoring 3-tuples query sequence identity matches seeds HSPs a 3-tuple For every 3-residue window, we get the set of 50 nearest neighbors. Use each word to get identity matches (seeds). Then extend the seed alignments as long as the score increases. neighborhood words database sequence BLAST HSPs alignment The best extended seeds are called HSPs (high scoring pairs). The top scoring HSP is picked first, then the second (as long as it falls "northwest" or "southeast" of the first.), and so on. BLAST search using NCBI •Open a web browser. •Go to NCBI-BLAST (www.ncbi.nlm.nih.gov/BLAST/) and select "# Nucleotide-nucleotide BLAST (blastn) " •Login to bioinf45 •type 'more ~bystroff/evidence.fasta' •Copy/paste the DNA sequence into the Blast sequence window. Select 'nr'. Select Descriptions=10, Alignments=10. Run it. Format it. •When the results are back, go to the bottom of the page. Hit "Select all" and "Get selected sequences" •continued..... In class exercise. BLAST search using SeqLab •start SeqLab •Using LookUp, Find sequences in PIR that match the keyword "R67". Check the results. Choose the PIR sequence. What is the accession number? •Get the sequence using File/Add sequences from/Databases, using the accession number •Run BLAST using this sequence. Be sure to search the protein databases. Set the cutoff to 10.0 •Add to Main list. Go to Main list, select it. Go to Editor. (Choose to Modify the sequences. This cuts off long ends) In class exercise. Multiple sequence alignment search using SeqLab •Select all sequences. Run ClustalW multiple alignment. •Extensions-->ClustalW (use the defaults) •When the job is done, save to Main list. Then select it, and go to the Editor. •You should now see a multiple sequence alignment. In class exercise.
